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Publications of year 2016

Articles in journal or book chapters

  1. Homa Ansari, Francesco De Zan, Alessandro Parizzi, Michael Eineder, Kanika Goel, and Nico Adam. Measuring 3-D Surface Motion With Future SAR Systems Based on Reflector Antennae. IEEE Geoscience and Remote Sensing Letters, 13(2):272-276, February 2016. Keyword(s): artificial satellites, radar interferometry, reflector antennas, remote sensing by radar, synthetic aperture radar, 3D surface motion measurement, SAR system, reflector antennae, interferometric synthetic aperture radar, 1D line-of-sight motion measurement, left-looking observation, right-looking observation, SAR acquisition mode, BiDiSAR, SuperSAR, electronic beam steering, squinted SAR geometry, satellite constellation, data processing, Synthetic aperture radar, Orbits, Geometry, Satellites, Motion measurement, Antenna measurements, Sensitivity, Azimuth shifts, error analysis, interferometric SAR (InSAR), SAR acquisition geometry, squinted SAR, 3-D surface motion, Azimuth shifts, error analysis, interferometric SAR (InSAR), SAR acquisition geometry, squinted SAR, 3-D surface motion.
    Abstract: A conventional interferometric synthetic aperture radar (SAR) system provides 1-D line-of-sight motion measurements from repeat-pass observations. Two-dimensional motions may be measured by combining two observations from ascending and descending geometries. The third motion component may be retrieved by adding a third geometry and/or by integrating along-track measurements although with much reduced precision compared to the other two components. Several options exist to improve the accuracy of retrieving the third motion component, such as combining left- and right-looking observations or exploiting recently proposed innovative SAR acquisition modes (BiDiSAR and SuperSAR). These options are, however, challenging for future SAR systems based on large reflector antennae, due to lack of capability to electronic beam steering or frequent toggle between left- and right-looking modes. Therefore, in this letter, we assess and compare the realistic acquisition scenarios for a reflector-based SAR in an attempt to optimize the achievable 3-D precision. Investigating the squinted SAR geometry as one of the feasible scenarios, we show that a squint of 13.5� will yield comparable performance to the left-looking acquisition, while further squinting outperforms this or other feasible configurations. As an optimum configuration for 3-D retrieval, the squinted acquisition is further elaborated: the different acquisition plans considering a constellation of two satellites as well as the challenges for data processing are addressed.

    @Article{ansariDeZanParizziEinederGoelAdamGRSL3DSurfaceMotionFromFutureSARSystems,
    author = {Ansari, Homa and De Zan, Francesco and Parizzi, Alessandro and Eineder, Michael and Goel, Kanika and Adam, Nico},
    title = {Measuring {3-D} Surface Motion With Future {SAR} Systems Based on Reflector Antennae},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2016},
    volume = {13},
    number = {2},
    pages = {272-276},
    month = {Feb},
    abstract = {A conventional interferometric synthetic aperture radar (SAR) system provides 1-D line-of-sight motion measurements from repeat-pass observations. Two-dimensional motions may be measured by combining two observations from ascending and descending geometries. The third motion component may be retrieved by adding a third geometry and/or by integrating along-track measurements although with much reduced precision compared to the other two components. Several options exist to improve the accuracy of retrieving the third motion component, such as combining left- and right-looking observations or exploiting recently proposed innovative SAR acquisition modes (BiDiSAR and SuperSAR). These options are, however, challenging for future SAR systems based on large reflector antennae, due to lack of capability to electronic beam steering or frequent toggle between left- and right-looking modes. Therefore, in this letter, we assess and compare the realistic acquisition scenarios for a reflector-based SAR in an attempt to optimize the achievable 3-D precision. Investigating the squinted SAR geometry as one of the feasible scenarios, we show that a squint of 13.5� will yield comparable performance to the left-looking acquisition, while further squinting outperforms this or other feasible configurations. As an optimum configuration for 3-D retrieval, the squinted acquisition is further elaborated: the different acquisition plans considering a constellation of two satellites as well as the challenges for data processing are addressed.},
    doi = {10.1109/LGRS.2015.2509440},
    file = {:ansariDeZanParizziEinederGoelAdamGRSL3DSurfaceMotionFromFutureSARSystems.pdf:PDF},
    keywords = {artificial satellites;radar interferometry;reflector antennas;remote sensing by radar;synthetic aperture radar;3D surface motion measurement;SAR system;reflector antennae;interferometric synthetic aperture radar;1D line-of-sight motion measurement;left-looking observation;right-looking observation;SAR acquisition mode;BiDiSAR;SuperSAR;electronic beam steering;squinted SAR geometry;satellite constellation;data processing;Synthetic aperture radar;Orbits;Geometry;Satellites;Motion measurement;Antenna measurements;Sensitivity;Azimuth shifts;error analysis;interferometric SAR (InSAR);SAR acquisition geometry;squinted SAR;3-D surface motion;Azimuth shifts;error analysis;interferometric SAR (InSAR);SAR acquisition geometry;squinted SAR;3-D surface motion},
    owner = {ofrey},
    
    }
    


  2. F. Banda, J. Dall, and S. Tebaldini. Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure. IEEE Transactions on Geoscience and Remote Sensing, 54(5):2832-2845, May 2016. Keyword(s): glaciology, remote sensing by radar, synthetic aperture radar, multipolarimetric P-band SAR tomography, subsurface ice structure, multipolarization synthetic aperture radar, glaciers, ice sheets, Earth Explorer mission BIOMASS, IceSAR 2012, TomoSAR techniques, southwest of Greenland, cryospheric remote sensing, Synthetic aperture radar, Ice, Tomography, Estimation, Image resolution, Scattering, BIOMASS, cryosphere, Greenland, synthetic aperture radar (SAR), tomography, BIOMASS, cryosphere, Greenland, synthetic aperture radar (SAR), tomography.
    Abstract: In this paper, first results concerning the characterization of the subsurface of ice sheets and glaciers through single and multipolarization synthetic aperture radar (SAR) tomography (TomoSAR) are illustrated. To this aim, the processing of data acquired in the framework of the European Space Agency IceSAR 2012 campaign is discussed. IceSAR 2012 was conceived so as to support the secondary objectives of the future Earth Explorer mission BIOMASS, which will be a SAR instrument with media penetration capabilities due to the use of the P-band frequency. In this regard, a tomographic study of ice was motivated by the fact that cryospheric remote sensing is of fundamental importance in order to understand more in depth the morphology and the dynamic processes regulating ice sheets. The main objective of the tomographic experiment of the campaign herein discussed was indeed to assess the capability of P-band SAR to retrieve any information about ice subsurface structure. Imaging has been achieved through TomoSAR techniques, applied to airborne multibaseline data acquired in the southwest of Greenland. Different imaging approaches are compared, and the main results achieved are presented: It is found that scattering in the upper layers of glacial subsurface can be achieved up to an extent of about 20-60 m, conditional on the different types of glaciological zone observed. Moreover, clear morphological structures have been found beneath the ice surface at one of the investigated sites.

    @Article{bandaDallTebaldiniTGRS2016SingleMultipolPBandTomoSubsurfaceIce,
    author = {F. {Banda} and J. {Dall} and S. {Tebaldini}},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {Single and Multipolarimetric {P}-Band {SAR} Tomography of Subsurface Ice Structure},
    year = {2016},
    issn = {1558-0644},
    month = may,
    number = {5},
    pages = {2832-2845},
    volume = {54},
    abstract = {In this paper, first results concerning the characterization of the subsurface of ice sheets and glaciers through single and multipolarization synthetic aperture radar (SAR) tomography (TomoSAR) are illustrated. To this aim, the processing of data acquired in the framework of the European Space Agency IceSAR 2012 campaign is discussed. IceSAR 2012 was conceived so as to support the secondary objectives of the future Earth Explorer mission BIOMASS, which will be a SAR instrument with media penetration capabilities due to the use of the P-band frequency. In this regard, a tomographic study of ice was motivated by the fact that cryospheric remote sensing is of fundamental importance in order to understand more in depth the morphology and the dynamic processes regulating ice sheets. The main objective of the tomographic experiment of the campaign herein discussed was indeed to assess the capability of P-band SAR to retrieve any information about ice subsurface structure. Imaging has been achieved through TomoSAR techniques, applied to airborne multibaseline data acquired in the southwest of Greenland. Different imaging approaches are compared, and the main results achieved are presented: It is found that scattering in the upper layers of glacial subsurface can be achieved up to an extent of about 20-60 m, conditional on the different types of glaciological zone observed. Moreover, clear morphological structures have been found beneath the ice surface at one of the investigated sites.},
    doi = {10.1109/TGRS.2015.2506399},
    keywords = {glaciology;remote sensing by radar;synthetic aperture radar;multipolarimetric P-band SAR tomography;subsurface ice structure;multipolarization synthetic aperture radar;glaciers;ice sheets;Earth Explorer mission BIOMASS;IceSAR 2012;TomoSAR techniques;southwest of Greenland;cryospheric remote sensing;Synthetic aperture radar;Ice;Tomography;Estimation;Image resolution;Scattering;BIOMASS;cryosphere;Greenland;synthetic aperture radar (SAR);tomography;BIOMASS;cryosphere;Greenland;synthetic aperture radar (SAR);tomography},
    owner = {ofrey},
    
    }
    


  3. David P. S. Bekaert, P. Segall, Tim J. Wright, and Andrew J. Hooper. A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling. Journal of Geophysical Research: Solid Earth, 121(3):2069-2086, March 2016.
    @Article{bekaertSegallWrightHooperAGUJGR2016NetworkInversionFilterCombiningGNSSandInSARforTectonicSlipModelling,
    author = {David P. S. Bekaert and P. Segall and Tim J. Wright and Andrew J. Hooper},
    journal = {Journal of Geophysical Research: Solid Earth},
    title = {A Network Inversion Filter combining {GNSS} and {InSAR} for tectonic slip modeling},
    year = {2016},
    month = {mar},
    number = {3},
    pages = {2069--2086},
    volume = {121},
    doi = {10.1002/2015jb012638},
    file = {:bekaertSegallWrightHooperAGUJGR2016NetworkInversionFilterCombiningGNSSandInSARforTectonicSlipModelling.pdf:PDF},
    owner = {ofrey},
    publisher = {American Geophysical Union ({AGU})},
    
    }
    


  4. Alessandra Budillon and Gilda Schirinzi. GLRT Based on Support Estimation for Multiple Scatterers Detection in SAR Tomography. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(3):1086-1094, March 2016. Keyword(s): SAR Processing, SAR Tomography, radar detection, radar receivers, radar resolution, synthetic aperture radar, tomography, GLRT detector, ROC curve, SAR tomography, Sup-GLRT, elevation direction, generalized likelihood ratio test detector, multiple scatterer detection, nominal system resolution, nominal system super-resolution, receiver operating characteristic curve, signal sparsity, signal support detection operation, signal support estimation operation, signal-to-noise ratio, subspace energy measurement, synthetic aperture radar, Earth, Estimation, Signal resolution, Spatial resolution, Synthetic aperture radar, Tomography, Generalized likelihood ratio test (GLRT), radar detection, sparse signals, synthetic aperture radar (SAR).
    Abstract: In this paper, a generalized likelihood ratio test (GLRT) detector, based on support estimation (Sup-GLRT), for multiple scatterers detection in SAR Tomography, is proposed. It incorporates, in the statistical model, a sparsity assumption of the signal in the elevation direction, which is always verified in practical cases for scarcely vegetated areas. The test consists of sequential steps: first the presence of scatterers is detected; then, the determination of the number of scatterers and the estimation of their positons is performed sequentially, one by one, by means of a signal support detection-estimation operation. The test proposed follows an approach similar to SGLRT, where decisions are taken based on subspace energy measurements, but it is derived following a different testing order and is investigated both at the nominal system resolution and in the super-resolution cases, showing in the latter case, a detection gain with respect to SGLRT. Sup-GLRT performance is evaluated in terms of receiver operating characteristic (ROC) curves for different signal-to-noise ratio values. Experimental results obtained on real COSMO-SkyMed data are shown.

    @Article{budillonSchirinziJSTARS2016Tomo,
    author = {Alessandra Budillon and Gilda Schirinzi},
    title = {{GLRT} Based on Support Estimation for Multiple Scatterers Detection in {SAR} Tomography},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2016},
    volume = {9},
    number = {3},
    pages = {1086-1094},
    month = mar,
    issn = {1939-1404},
    abstract = {In this paper, a generalized likelihood ratio test (GLRT) detector, based on support estimation (Sup-GLRT), for multiple scatterers detection in SAR Tomography, is proposed. It incorporates, in the statistical model, a sparsity assumption of the signal in the elevation direction, which is always verified in practical cases for scarcely vegetated areas. The test consists of sequential steps: first the presence of scatterers is detected; then, the determination of the number of scatterers and the estimation of their positons is performed sequentially, one by one, by means of a signal support detection-estimation operation. The test proposed follows an approach similar to SGLRT, where decisions are taken based on subspace energy measurements, but it is derived following a different testing order and is investigated both at the nominal system resolution and in the super-resolution cases, showing in the latter case, a detection gain with respect to SGLRT. Sup-GLRT performance is evaluated in terms of receiver operating characteristic (ROC) curves for different signal-to-noise ratio values. Experimental results obtained on real COSMO-SkyMed data are shown.},
    doi = {10.1109/JSTARS.2015.2494376},
    file = {:budillonSchirinziJSTARS2016Tomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, radar detection;radar receivers;radar resolution;synthetic aperture radar;tomography;GLRT detector;ROC curve;SAR tomography;Sup-GLRT;elevation direction;generalized likelihood ratio test detector;multiple scatterer detection;nominal system resolution;nominal system super-resolution;receiver operating characteristic curve;signal sparsity;signal support detection operation;signal support estimation operation;signal-to-noise ratio;subspace energy measurement;synthetic aperture radar;Earth;Estimation;Signal resolution;Spatial resolution;Synthetic aperture radar;Tomography;Generalized likelihood ratio test (GLRT);radar detection;sparse signals;synthetic aperture radar (SAR)},
    owner = {ofrey},
    pdf = {../../../docs/budillonSchirinziJSTARS2016Tomo.pdf},
    
    }
    


  5. Mariko S. Burgin, Uday K. Khankhoje, Xueyang Duan, and Mahta Moghaddam. Generalized Terrain Topography in Radar Scattering Models. IEEE Transactions on Geoscience and Remote Sensing, 54(7):3944-3952, July 2016. Keyword(s): terrain mapping, topography (Earth), vegetation, N-layered soil structure, evergreen forest, extended boundary condition method, modular model, multilayered multispecies vegetation model, overlying vegetation, radar scattering models, radar wave interactions, terrain topography, topographic slopes, Backscatter, Radar, Radar scattering, Surface topography, Vegetation mapping, Electromagnetic scattering, modeling, radar terrain factors, remote sensing, vegetation.
    Abstract: Modeling of terrain topography is crucial for vegetated areas given that even small slopes impact and alter the radar wave interactions between the ground and the overlying vegetation. Current missions either exclude pixels with large topographic slopes or disregard the terrain topography entirely, potentially accumulating substantial modeling errors and therefore impacting the retrieval performance over such sloped pixels. The underlying terrain topography needs to be considered and modeled to obtain a truly general and accurate radar scattering model. In this paper, a flexible and modular model is developed: the vegetation is considered by a multilayered multispecies vegetation model capable of representing a wide range of vegetation cover types ranging from bare soil to dense forests. The ground is incorporated with the stabilized extended boundary condition method, allowing the representation of an N-layered soil structure with rough interfaces. Terrain topography is characterized by a 2-D slope with two tilt angles (alpha, beta). Simulation results for an evergreen forest show the impact of a 2-D slope for a range of tilt angles: a 10 deg tilt in the plane of incidence translates to a change of up to 15 dB in 1111, 10 dB in VV, and 1.5 dB in 11V for the total radar backscatter. Terrain topography is shown to be crucial for accurate forward modeling, especially over forested areas.

    @Article{burginKhankhojeDuanMoghaddamTGRS2016TerrainTopographyRadarScatteringModels,
    author = {Mariko S. Burgin and Uday K. Khankhoje and Xueyang Duan and Mahta Moghaddam},
    title = {Generalized Terrain Topography in Radar Scattering Models},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2016},
    volume = {54},
    number = {7},
    pages = {3944-3952},
    month = jul,
    issn = {0196-2892},
    abstract = {Modeling of terrain topography is crucial for vegetated areas given that even small slopes impact and alter the radar wave interactions between the ground and the overlying vegetation. Current missions either exclude pixels with large topographic slopes or disregard the terrain topography entirely, potentially accumulating substantial modeling errors and therefore impacting the retrieval performance over such sloped pixels. The underlying terrain topography needs to be considered and modeled to obtain a truly general and accurate radar scattering model. In this paper, a flexible and modular model is developed: the vegetation is considered by a multilayered multispecies vegetation model capable of representing a wide range of vegetation cover types ranging from bare soil to dense forests. The ground is incorporated with the stabilized extended boundary condition method, allowing the representation of an N-layered soil structure with rough interfaces. Terrain topography is characterized by a 2-D slope with two tilt angles (alpha, beta). Simulation results for an evergreen forest show the impact of a 2-D slope for a range of tilt angles: a 10 deg tilt in the plane of incidence translates to a change of up to 15 dB in 1111, 10 dB in VV, and 1.5 dB in 11V for the total radar backscatter. Terrain topography is shown to be crucial for accurate forward modeling, especially over forested areas.},
    doi = {10.1109/TGRS.2016.2532123},
    file = {:burginKhankhojeDuanMoghaddamTGRS2016TerrainTopographyRadarScatteringModels.pdf:PDF},
    keywords = {terrain mapping;topography (Earth);vegetation;N-layered soil structure;evergreen forest;extended boundary condition method;modular model;multilayered multispecies vegetation model;overlying vegetation;radar scattering models;radar wave interactions;terrain topography;topographic slopes;Backscatter;Radar;Radar scattering;Surface topography;Vegetation mapping;Electromagnetic scattering;modeling;radar terrain factors;remote sensing;vegetation},
    
    }
    


  6. Mariko S. Burgin and Jakob J. van Zyl. Analysis of Polarimetric Radar Data and Soil Moisture From Aquarius: Towards a Regression-Based Soil Moisture Estimation Algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8):3497-3504, August 2016. Keyword(s): Backscatter, Data models, Estimation, L-band, Radar, Soil moisture, Vegetation mapping, Moisture, polarimetric radar, soil, synthetic aperture radar (SAR), time series.
    Abstract: Many soil moisture radar retrieval algorithms depend on substantial amounts of ancillary data, such as land cover type and soil composition. To address this issue, we examine and expand an empirical approach by Kim and van Zyl as an alternative; it describes radar backscatter of a vegetated scene as a linear function of volumetric soil moisture, thus reducing the dependence on ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine the two polarization dependent parameters on a global scale and on a weekly basis. We propose a look-up table based soil moisture estimation approach; it is promising due to its simplicity and independence of ancillary data. However, the estimation performance is found to be impacted by the used land cover classification scheme. Our results show that the sensitivity of the radar signal to soil moisture changes seasonally, and that the variation differs depending on vegetation class. While this seasonal variation can be relatively small, it must be properly accounted for as it impacts the soil moisture retrieval accuracy.

    @Article{burginVanZylJSTARS2016SoilMoisturePolSAR,
    author = {Mariko S. Burgin and Jakob J. van Zyl},
    title = {Analysis of Polarimetric Radar Data and Soil Moisture From Aquarius: Towards a Regression-Based Soil Moisture Estimation Algorithm},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2016},
    volume = {9},
    number = {8},
    pages = {3497-3504},
    month = aug,
    issn = {1939-1404},
    abstract = {Many soil moisture radar retrieval algorithms depend on substantial amounts of ancillary data, such as land cover type and soil composition. To address this issue, we examine and expand an empirical approach by Kim and van Zyl as an alternative; it describes radar backscatter of a vegetated scene as a linear function of volumetric soil moisture, thus reducing the dependence on ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine the two polarization dependent parameters on a global scale and on a weekly basis. We propose a look-up table based soil moisture estimation approach; it is promising due to its simplicity and independence of ancillary data. However, the estimation performance is found to be impacted by the used land cover classification scheme. Our results show that the sensitivity of the radar signal to soil moisture changes seasonally, and that the variation differs depending on vegetation class. While this seasonal variation can be relatively small, it must be properly accounted for as it impacts the soil moisture retrieval accuracy.},
    doi = {10.1109/JSTARS.2016.2526899},
    file = {:burginVanZylJSTARS2016SoilMoisturePolSAR.pdf:PDF},
    keywords = {Backscatter;Data models;Estimation;L-band;Radar;Soil moisture;Vegetation mapping;Moisture;polarimetric radar;soil;synthetic aperture radar (SAR);time series},
    
    }
    


  7. Ning Cao, Hyongki Lee, and H. C. Jung. A Phase-Decomposition-Based PSInSAR Processing Method. IEEE Transactions on Geoscience and Remote Sensing, 54(2):1074-1090, February 2016. Keyword(s): radar interferometry, synthetic aperture radar, coherence, distributed scatterer, eigendecomposition, measurement points, multiple scattering mechanisms, persistent scatterer network density, phase-decomposition-based persistent scatterer InSAR method, spatial density, Coherence, Covariance matrices, Decision support systems, Eigenvalues and eigenfunctions, Synthetic aperture radar, Urban areas, Differential interferometric synthetic aperture radar (DInSAR), distributed scatterer (DS) interferometry, persistent scatterer (PS) interferometry (PSI), synthetic aperture radar (SAR).
    Abstract: A phase-decomposition-based persistent scatterer (PS) InSAR (PD-PSInSAR) method is developed in this paper to improve coherence and spatial density of measurement points (MPs). In order to improve PS network density, a distributed scatterer (DS) has been utilized in some advanced PSInSAR process, such as SqueeSAR. In addition to the conventional DS that consists of independent small scatterers with a uniform scattering mechanism, processing the DSs dominated by two or more scattering mechanisms is a promising way to improve MP density. Estimating phases from DS with multiple scattering mechanisms is difficult for many DS algorithms because of the interference between different scattering mechanisms. Recently, a covariance-matrix-decomposition-based method, which is named Component extrAction and sElection SAR (CAESAR), is proposed to extract different scattering components from the analysis of the covariance matrix. Instead of using a covariance matrix, the PD-PSInSAR in this study is developed to perform eigendecomposition on a coherence matrix, in order to estimate the phases corresponding to the different scattering mechanisms, and then to implement these estimated phases in a conventional PSInSAR process. The major benefit of using a coherence matrix rather than a covariance matrix is to compensate the amplitude unbalances among SAR images. A detailed study of comparison among SqueeSAR, CAESAR, and PD-PSInSAR is also performed in this study. It has been found that these three methods share very similar mathematic forms with different weight values. The PD-PSInSAR method is implemented to estimate land deformation over the greater Houston area using Envisat ASAR images, which verifies that the proposed method can detect more MPs and provide better coherences.

    @Article{caoLeeJungTGRS2016PhaseDecompositionPSInSAR,
    author = {Ning Cao and Hyongki Lee and H. C. Jung},
    title = {A Phase-Decomposition-Based {PSInSAR} Processing Method},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2016},
    volume = {54},
    number = {2},
    month = feb,
    pages = {1074-1090},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2015.2473818},
    abstract = {A phase-decomposition-based persistent scatterer (PS) InSAR (PD-PSInSAR) method is developed in this paper to improve coherence and spatial density of measurement points (MPs). In order to improve PS network density, a distributed scatterer (DS) has been utilized in some advanced PSInSAR process, such as SqueeSAR. In addition to the conventional DS that consists of independent small scatterers with a uniform scattering mechanism, processing the DSs dominated by two or more scattering mechanisms is a promising way to improve MP density. Estimating phases from DS with multiple scattering mechanisms is difficult for many DS algorithms because of the interference between different scattering mechanisms. Recently, a covariance-matrix-decomposition-based method, which is named Component extrAction and sElection SAR (CAESAR), is proposed to extract different scattering components from the analysis of the covariance matrix. Instead of using a covariance matrix, the PD-PSInSAR in this study is developed to perform eigendecomposition on a coherence matrix, in order to estimate the phases corresponding to the different scattering mechanisms, and then to implement these estimated phases in a conventional PSInSAR process. The major benefit of using a coherence matrix rather than a covariance matrix is to compensate the amplitude unbalances among SAR images. A detailed study of comparison among SqueeSAR, CAESAR, and PD-PSInSAR is also performed in this study. It has been found that these three methods share very similar mathematic forms with different weight values. The PD-PSInSAR method is implemented to estimate land deformation over the greater Houston area using Envisat ASAR images, which verifies that the proposed method can detect more MPs and provide better coherences.},
    keywords = {radar interferometry;synthetic aperture radar;coherence;distributed scatterer;eigendecomposition;measurement points;multiple scattering mechanisms;persistent scatterer network density;phase-decomposition-based persistent scatterer InSAR method;spatial density;Coherence;Covariance matrices;Decision support systems;Eigenvalues and eigenfunctions;Synthetic aperture radar;Urban areas;Differential interferometric synthetic aperture radar (DInSAR);distributed scatterer (DS) interferometry;persistent scatterer (PS) interferometry (PSI);synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  8. S. K. Chan, R. Bindlish, P. E. O'Neill, E. Njoku, T. Jackson, A. Colliander, F. Chen, Mariko S. Burgin, S. Dunbar, J. Piepmeier, S. Yueh, D. Entekhabi, M. H. Cosh, T. Caldwell, J. Walker, X. Wu, A. Berg, T. Rowlandson, A. Pacheco, H. McNairn, M. Thibeault, J. Martinez-Fernandez, Angel Gonzalez-Zamora, M. Seyfried, D. Bosch, P. Starks, D. Goodrich, J. Prueger, M. Palecki, E. E. Small, M. Zreda, J. C. Calvet, W. T. Crow, and Y. Kerr. Assessment of the SMAP Passive Soil Moisture Product. IEEE Transactions on Geoscience and Remote Sensing, 54(8):4994-5007, August 2016. Keyword(s): hydrological techniques, moisture, remote sensing by radar, soil, L-band radar, L-band radiometer, Level 2 Passive Soil Moisture Product, NASA Distributed Active Archive Center at the National Snow and Ice Data Center, NASA SMAP satellite mission, National Aeronautics and Space Administration, SMAP Passive Soil Moisture product, V-pol Single Channel Algorithm, freeze-thaw state, high-resolution soil moisture global mapping, radar irrecoverable hardware failure, radiometer-only soil moisture product, soil moisture estimates, soil moisture retrievals, Agriculture, Data models, Microwave radiometry, NASA, Soil moisture, Spatial resolution, Brightness temperature, L-band, Level 2 Passive Soil Moisture Product, Level 3 Daily Composite Version, Soil Moisture Active Passive (SMAP), land emission, passive microwave remote sensing, soil moisture, tau-omega model, validation.
    Abstract: The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.

    @Article{chanEtAlTGRS2016SMAPPassiveSoilMoistureProduct,
    author = {S. K. Chan and R. Bindlish and O'Neill,P. E. and E. Njoku and T. Jackson and A. Colliander and F. Chen and Mariko S. Burgin and S. Dunbar and J. Piepmeier and S. Yueh and D. Entekhabi and M. H. Cosh and T. Caldwell and J. Walker and X. Wu and A. Berg and T. Rowlandson and A. Pacheco and H. McNairn and M. Thibeault and J. Martinez-Fernandez and Gonzalez-Zamora, Angel and M. Seyfried and D. Bosch and P. Starks and D. Goodrich and J. Prueger and M. Palecki and E. E. Small and M. Zreda and J. C. Calvet and W. T. Crow and Y. Kerr},
    title = {Assessment of the {SMAP} Passive Soil Moisture Product},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2016},
    volume = {54},
    number = {8},
    pages = {4994-5007},
    month = aug,
    issn = {0196-2892},
    abstract = {The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.},
    doi = {10.1109/TGRS.2016.2561938},
    file = {:chanEtAlTGRS2016SMAPPassiveSoilMoistureProduct.pdf:PDF},
    keywords = {hydrological techniques;moisture;remote sensing by radar;soil;L-band radar;L-band radiometer;Level 2 Passive Soil Moisture Product;NASA Distributed Active Archive Center at the National Snow and Ice Data Center;NASA SMAP satellite mission;National Aeronautics and Space Administration;SMAP Passive Soil Moisture product;V-pol Single Channel Algorithm;freeze-thaw state;high-resolution soil moisture global mapping;radar irrecoverable hardware failure;radiometer-only soil moisture product;soil moisture estimates;soil moisture retrievals;Agriculture;Data models;Microwave radiometry;NASA;Soil moisture;Spatial resolution;Brightness temperature;L-band;Level 2 Passive Soil Moisture Product;Level 3 Daily Composite Version;Soil Moisture Active Passive (SMAP);land emission;passive microwave remote sensing;soil moisture;tau-omega model;validation},
    
    }
    


  9. Michele Crosetto, Oriol Monserrat, Mara Cuevas-Gonzlez, Nria Devanthry, and Bruno Crippa. Persistent Scatterer Interferometry: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 115:78-89, 2016. Note: Theme issue State-of-the-art in photogrammetry, remote sensing and spatial information science. Keyword(s): SAR Processing, Persistent Scatterer Interferometry, PSI, Remote sensing, Radar, SAR, Monitoring, Deformation.
    Abstract: Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth's surface over time. Specifically, PSI is a radar-based technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.

    @Article{crosettoMonserratCuevasGonzalesDevantheryCrippaISPRS2016PSIReview,
    author = {Michele Crosetto and Oriol Monserrat and Mar\'ia Cuevas-Gonz\'alez and N\'uria Devanth\'ery and Bruno Crippa},
    title = {Persistent Scatterer Interferometry: A review},
    journal = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
    year = {2016},
    volume = {115},
    pages = {78-89},
    issn = {0924-2716},
    note = {Theme issue State-of-the-art in photogrammetry, remote sensing and spatial information science},
    abstract = {Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth's surface over time. Specifically, PSI is a radar-based technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.},
    doi = {http://dx.doi.org/10.1016/j.isprsjprs.2015.10.011},
    file = {:crosettoMonserratCuevasGonzalesDevantheryCrippaISPRS2016PSIReview.pdf:PDF},
    keywords = {SAR Processing, Persistent Scatterer Interferometry, PSI, Remote sensing,Radar,SAR, Monitoring,Deformation},
    owner = {ofrey},
    pdf = {../../../docs/crosettoMonserratCuevasGonzalesDevantheryCrippaISPRS2016PSIReview.pdf},
    url = {http://www.sciencedirect.com/science/article/pii/S0924271615002415},
    
    }
    


  10. Brent G. Delbridge, Roland Brgmann, Eric Fielding, Scott Hensley, and William H. Schulz. Three-dimensional surface deformation derived from airborne interferometric UAVSAR: Application to the Slumgullion Landslide. Journal of Geophysical Research: Solid Earth, 121(5):3951-3977, 2016. Keyword(s): SAR Processing, UAVSAR, landslide, Slumgullion, InSAR, geodesy, inversion, DInSAR, Airborne DInSAR, Surface Displacement, Deformation, Airborne SAR, L-band.
    Abstract: Abstract In order to provide surface geodetic measurements with landslide-wide spatial coverage, we develop and validate a method for the characterization of 3-D surface deformation using the unique capabilities of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne repeat-pass radar interferometry system. We apply our method at the well-studied Slumgullion Landslide, which is 3.9 km long and moves persistently at rates up to approx. 2 cm/day. A comparison with concurrent GPS measurements validates this method and shows that it provides reliable and accurate 3-D surface deformation measurements. The UAVSAR-derived vector velocity field measurements accurately capture the sharp boundaries defining previously identified kinematic units and geomorphic domains within the landslide. We acquired data across the landslide during spring and summer and identify that the landslide moves more slowly during summer except at its head, presumably in response to spatiotemporal variations in snowmelt infiltration. In order to constrain the mechanics controlling landslide motion from surface velocity measurements, we present an inversion framework for the extraction of slide thickness and basal geometry from dense 3-D surface velocity fields. We find that the average depth of the Slumgullion Landslide is 7.5 m, several meters less than previous depth estimates. We show that by considering a viscoplastic rheology, we can derive tighter theoretical bounds on the rheological parameter relating mean horizontal flow rate to surface velocity. Using inclinometer data for slow-moving, clay-rich landslides across the globe, we find a consistent value for the rheological parameter of 0.85 +/- 0.08.

    @Article{delbridgeBurgmannFieldingHensleySchulzJGR2016AirborneDINSARwithUAVSARSlumgullionLandslide,
    author = {Delbridge, Brent G. and B\"urgmann, Roland and Fielding, Eric and Hensley, Scott and Schulz, William H.},
    journal = {Journal of Geophysical Research: Solid Earth},
    title = {Three-dimensional surface deformation derived from airborne interferometric {UAVSAR}: Application to the {Slumgullion} Landslide},
    year = {2016},
    number = {5},
    pages = {3951-3977},
    volume = {121},
    abstract = {Abstract In order to provide surface geodetic measurements with landslide-wide spatial coverage, we develop and validate a method for the characterization of 3-D surface deformation using the unique capabilities of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne repeat-pass radar interferometry system. We apply our method at the well-studied Slumgullion Landslide, which is 3.9 km long and moves persistently at rates up to approx. 2 cm/day. A comparison with concurrent GPS measurements validates this method and shows that it provides reliable and accurate 3-D surface deformation measurements. The UAVSAR-derived vector velocity field measurements accurately capture the sharp boundaries defining previously identified kinematic units and geomorphic domains within the landslide. We acquired data across the landslide during spring and summer and identify that the landslide moves more slowly during summer except at its head, presumably in response to spatiotemporal variations in snowmelt infiltration. In order to constrain the mechanics controlling landslide motion from surface velocity measurements, we present an inversion framework for the extraction of slide thickness and basal geometry from dense 3-D surface velocity fields. We find that the average depth of the Slumgullion Landslide is 7.5 m, several meters less than previous depth estimates. We show that by considering a viscoplastic rheology, we can derive tighter theoretical bounds on the rheological parameter relating mean horizontal flow rate to surface velocity. Using inclinometer data for slow-moving, clay-rich landslides across the globe, we find a consistent value for the rheological parameter of 0.85 +/- 0.08.},
    doi = {https://doi.org/10.1002/2015JB012559},
    eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015JB012559},
    keywords = {SAR Processing, UAVSAR, landslide, Slumgullion, InSAR, geodesy, inversion, DInSAR, Airborne DInSAR, Surface Displacement, Deformation, Airborne SAR, L-band},
    owner = {ofrey},
    url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2015JB012559},
    
    }
    


  11. G. Gomba, A. Parizzi, F. De Zan, M. Eineder, and R. Bamler. Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method. IEEE_J_GRS, 54(3):1446-1461, March 2016. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, ionospheric electromagnetic wave propagation, synthetic aperture radar, L-band interferograms, L-band synthetic aperture radar interferometric pairs, SAR interferograms, advanced land observing satellite phased-array, differential ionospheric path delay, geophysical processes, ground deformation signals, ionospheric effects operational compensation, ionospheric phase, split-spectrum method, tropospheric path delay, Accuracy, Azimuth, Coherence, Delays, Estimation, Ionosphere, Synthetic aperture radar, Interferometric synthetic aperture radar (InSAR), ionosphere estimation, split spectrum, synthetic aperture radar (SAR) ionospheric effects.
    Abstract: The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor.

    @Article{gombaParizziDeZanEinederBamlerTGRS2016IonoSplitSpectrumInSAR,
    author = {G. Gomba and A. Parizzi and F. De Zan and M. Eineder and R. Bamler},
    title = {Toward Operational Compensation of Ionospheric Effects in {SAR} Interferograms: The Split-Spectrum Method},
    journal = IEEE_J_GRS,
    year = {2016},
    volume = {54},
    number = {3},
    pages = {1446--1461},
    month = mar,
    issn = {0196-2892},
    abstract = {The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor.},
    doi = {10.1109/TGRS.2015.2481079},
    file = {:gombaParizziDeZanEinederBamlerTGRS2016IonoSplitSpectrumInSAR.pdf:PDF},
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry,ionospheric electromagnetic wave propagation, synthetic aperture radar, L-band interferograms, L-band synthetic aperture radar interferometric pairs, SAR interferograms, advanced land observing satellite phased-array, differential ionospheric path delay, geophysical processes, ground deformation signals, ionospheric effects operational compensation, ionospheric phase, split-spectrum method, tropospheric path delay, Accuracy, Azimuth, Coherence, Delays, Estimation, Ionosphere, Synthetic aperture radar, Interferometric synthetic aperture radar (InSAR), ionosphere estimation, split spectrum, synthetic aperture radar (SAR) ionospheric effects},
    owner = {ofrey},
    
    }
    


  12. Scott Hensley, D. Moller, S. Oveisgharan, T. Michel, and X. Wu. Ka-Band Mapping and Measurements of Interferometric Penetration of the Greenland Ice Sheets by the GLISTIN Radar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(6):2436-2450, June 2016. Keyword(s): Global Positioning System, geophysical image processing, hydrological techniques, ice, image segmentation, meteorological radar, optical radar, radar interferometry, snow, synthetic aperture radar, topography (Earth), Antarctica, Earth environment, GLISTIN elevation measurement, GLISTIN instrument, GLISTIN radar, Greenland ice sheet, Jakobshavn glacier area, Ka-band cross-track interferometric radar, Ka-band mapping, NASA GLISTIN Ka-band interferometric radar, NASA Wallop airborne terrain mapper lidar measurement, climate change, ice cap topography, ice surface topography, image mosaic, interferometric penetration, interferometric penetration measurement, interferometric radar mapping system, kinematic GPS survey measurement, lidar, optical system, swath topographic measurement, Ice, Instruments, Laser radar, Sea measurements, Snow, Surfaces, Glaciers, Ka-band, ice sheets, interferometry, penetration, radar.
    @Article{hensleyMollerOveisgharanMichelWuJSTARS2016KaBandInSARGreenlandGLISTINRadar,
    author = {Scott Hensley and D. Moller and S. Oveisgharan and T. Michel and X. Wu},
    title = {{K}a-Band Mapping and Measurements of Interferometric Penetration of the {Greenland} Ice Sheets by the {GLISTIN} Radar},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2016},
    volume = {9},
    number = {6},
    pages = {2436--2450},
    month = jun,
    issn = {1939-1404},
    doi = {10.1109/JSTARS.2016.2560626},
    file = {:hensleyMollerOveisgharanMichelWuJSTARS2016KaBandInSARGreenlandGLISTINRadar.pdf:PDF},
    keywords = {Global Positioning System, geophysical image processing, hydrological techniques, ice, image segmentation, meteorological radar, optical radar, radar interferometry, snow, synthetic aperture radar, topography (Earth), Antarctica, Earth environment, GLISTIN elevation measurement, GLISTIN instrument, GLISTIN radar, Greenland ice sheet, Jakobshavn glacier area, Ka-band cross-track interferometric radar, Ka-band mapping, NASA GLISTIN Ka-band interferometric radar, NASA Wallop airborne terrain mapper lidar measurement, climate change, ice cap topography, ice surface topography, image mosaic, interferometric penetration, interferometric penetration measurement, interferometric radar mapping system, kinematic GPS survey measurement, lidar, optical system, swath topographic measurement, Ice, Instruments, Laser radar, Sea measurements, Snow, Surfaces, Glaciers, Ka-band, ice sheets, interferometry, penetration, radar},
    owner = {ofrey},
    
    }
    


  13. Fabrizio Lombardini and Federico Viviani. Single-look light-burden superresolution differential SAR tomography. Electronics Letters, 52(7):557-558, 2016. Keyword(s): SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban remote sensing, array signal processing, image sampling, radar imaging, radar interferometry, radar resolution, spectral analysis, synthetic aperture radar, 2D baseline-time spectral analysis framework, adaptive 2D spectral estimation, coherent multilooking processing, complex nonstationary scenes, complex-valued synthetic aperture radar data, elevation beamforming, full range-azimuth resolution products, full-3D imaging, height-velocity sidelobe reduction, layover scatterers, mature differential interferometry, multibaseline interferometry, satellites, single-look adaptive Diff-Tomo processor, single-look light-burden superresolution differential SAR tomography, sparse sampling, spatial spectral estimation.
    Abstract: Research and application is spreading of techniques of coherent combination of complex-valued synthetic aperture radar (SAR) data to extract rich information even on complex observed scenes, fully exploiting existing SAR data archives, and new satellites. Among such techniques, SAR tomography stems from multibaseline interferometry to achieve full-3D imaging through elevation beamforming (spatial spectral estimation). The Tomo concept has been integrated with the mature differential interferometry, producing the new differential tomography (Diff-Tomo) processing mode, that allows `opening' the SAR cells in complex non-stationary scenes, resolving multiple heights and slow deformation velocities of layover scatterers. Consequently, the operational capability limit of differential interferometry to the single scatterer case is overcome. Diff-Tomo processing is cast in a 2D baseline-time spectral analysis framework, with sparse sampling. The use of adaptive 2D spectral estimation has demonstrated to allow joint baseline-time processing with reduced sidelobes and enhanced height-velocity resolution at low computational burden. However, this method requires coherent multilooking processing, thus does not produce full range-azimuth resolution products, as it would be desirable for urban applications. A new single-look adaptive Diff-Tomo processor is presented and tested with satellite data, allowing full range-azimuth resolution together with height-velocity sidelobe reduction and superresolution capabilities and the low computational burden.

    @Article{lombardiniVivianiElectronicsLetter2016SingleLookSuperResolutionTomo,
    author = {Fabrizio Lombardini and Federico Viviani},
    title = {Single-look light-burden superresolution differential {SAR} tomography},
    journal = {Electronics Letters},
    year = {2016},
    volume = {52},
    number = {7},
    pages = {557-558},
    issn = {0013-5194},
    abstract = {Research and application is spreading of techniques of coherent combination of complex-valued synthetic aperture radar (SAR) data to extract rich information even on complex observed scenes, fully exploiting existing SAR data archives, and new satellites. Among such techniques, SAR tomography stems from multibaseline interferometry to achieve full-3D imaging through elevation beamforming (spatial spectral estimation). The Tomo concept has been integrated with the mature differential interferometry, producing the new differential tomography (Diff-Tomo) processing mode, that allows `opening' the SAR cells in complex non-stationary scenes, resolving multiple heights and slow deformation velocities of layover scatterers. Consequently, the operational capability limit of differential interferometry to the single scatterer case is overcome. Diff-Tomo processing is cast in a 2D baseline-time spectral analysis framework, with sparse sampling. The use of adaptive 2D spectral estimation has demonstrated to allow joint baseline-time processing with reduced sidelobes and enhanced height-velocity resolution at low computational burden. However, this method requires coherent multilooking processing, thus does not produce full range-azimuth resolution products, as it would be desirable for urban applications. A new single-look adaptive Diff-Tomo processor is presented and tested with satellite data, allowing full range-azimuth resolution together with height-velocity sidelobe reduction and superresolution capabilities and the low computational burden.},
    doi = {10.1049/el.2015.3414},
    file = {:lombardiniVivianiElectronicsLetter2016SingleLookSuperResolutionTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban remote sensing, array signal processing;image sampling;radar imaging;radar interferometry;radar resolution;spectral analysis;synthetic aperture radar;2D baseline-time spectral analysis framework;adaptive 2D spectral estimation;coherent multilooking processing;complex nonstationary scenes;complex-valued synthetic aperture radar data;elevation beamforming;full range-azimuth resolution products;full-3D imaging;height-velocity sidelobe reduction;layover scatterers;mature differential interferometry;multibaseline interferometry;satellites;single-look adaptive Diff-Tomo processor;single-look light-burden superresolution differential SAR tomography;sparse sampling;spatial spectral estimation},
    pdf = {../../../docs/lombardiniVivianiElectronicsLetter2016SingleLookSuperResolutionTomo.pdf},
    
    }
    


  14. Paco Lopez-Dekker, Marc Rodriguez-Cassola, Francesco De Zan, Gerhard Krieger, and Alberto Moreira. Correlating Synthetic Aperture Radar (CoSAR). IEEE Trans. Geosci. Remote Sens., 54(4):2268-2284, April 2016. Keyword(s): SAR Processing, geosynchronous SAR, geosynchronous orbit, Correlating SAR, CoSAR, Doppler effect, Doppler radar, Radar imaging, Sea surface, Surface topography, Synthetic aperture radar, Bistatic radar, ocean currents, sea level, sea surface, synthetic aperture radar, van Cittert-Zernike.
    Abstract: This paper presents the correlating synthetic aperture radar (CoSAR) technique, a novel radar imaging concept to observe statistical properties of fast decorrelating surfaces. A CoSAR system consists of two radars with a relative motion in the along-track (cross-range) dimension. The spatial autocorrelation function of the scattered signal can be estimated by combining quasi-simultaneously received radar echoes. By virtue of the Van Cittert-Zernike theorem, estimates of this autocorrelation function for different relative positions can be processed by generating images of several properties of the scene, including the normalized radar cross section, Doppler velocities, and surface topography. Aside from the geometric performance, a central aspect of this paper is a theoretical derivation of the radiometric performance of CoSAR. The radiometric quality is proportional to the number of independent samples available for the estimation of the spatial correlation, and to the ratio between the CoSAR azimuth resolution and the real-aperture resolution. A CoSAR mission concept is provided where two geosynchronous radar satellites fly at opposing sides of a quasi-circular trajectory. Such a mission could provide bidaily images of the ocean backscatter, mean Doppler, and surface topography at resolutions on the order of 500 m over wide areas.

    @Article{lopezDekkerRodriguezCassolaDeZanKriegerMoreiraTGRS2016CoSAR,
    author = {Lopez-Dekker, Paco and Rodriguez-Cassola, Marc and De Zan, Francesco and Krieger, Gerhard and Moreira, Alberto},
    title = {Correlating Synthetic Aperture Radar {(CoSAR)}},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2016},
    volume = {54},
    number = {4},
    pages = {2268-2284},
    month = apr,
    issn = {0196-2892},
    abstract = {This paper presents the correlating synthetic aperture radar (CoSAR) technique, a novel radar imaging concept to observe statistical properties of fast decorrelating surfaces. A CoSAR system consists of two radars with a relative motion in the along-track (cross-range) dimension. The spatial autocorrelation function of the scattered signal can be estimated by combining quasi-simultaneously received radar echoes. By virtue of the Van Cittert-Zernike theorem, estimates of this autocorrelation function for different relative positions can be processed by generating images of several properties of the scene, including the normalized radar cross section, Doppler velocities, and surface topography. Aside from the geometric performance, a central aspect of this paper is a theoretical derivation of the radiometric performance of CoSAR. The radiometric quality is proportional to the number of independent samples available for the estimation of the spatial correlation, and to the ratio between the CoSAR azimuth resolution and the real-aperture resolution. A CoSAR mission concept is provided where two geosynchronous radar satellites fly at opposing sides of a quasi-circular trajectory. Such a mission could provide bidaily images of the ocean backscatter, mean Doppler, and surface topography at resolutions on the order of 500 m over wide areas.},
    doi = {10.1109/TGRS.2015.2498707},
    file = {:lopezDekkerRodriguezCassolaDeZanKriegerMoreiraTGRS2016CoSAR.pdf:PDF},
    keywords = {SAR Processing, geosynchronous SAR, geosynchronous orbit, Correlating SAR, CoSAR, Doppler effect;Doppler radar;Radar imaging;Sea surface;Surface topography;Synthetic aperture radar;Bistatic radar;ocean currents;sea level;sea surface;synthetic aperture radar, van Cittert-Zernike},
    owner = {ofrey},
    pdf = {../../../docs/lopezDekkerRodriguezCassolaDeZanKriegerMoreiraTGRS2016CoSAR.pdf},
    
    }
    


  15. Jun Maeda, Takato Suzuki, Masato Furuya, and Kosuke Heki. Imaging the midlatitude sporadic E plasma patches with a coordinated observation of spaceborne InSAR and GPS total electron content. Geophysical Research Letters, 43(4):1419-1425, 2016. Keyword(s): sporadic E, GPS, total electron content, synthetic aperture radar, Kelvin-Helmholtz instability.
    Abstract: Kilometer-scale fine structures of midlatitude sporadic E (Es) plasma patches have been directly imaged for the first time by an interferogram derived from L band Advanced Land Observation Satellite/Phased Array-type L band Synthetic Aperture Radar data obtained over southwestern Japan. The synthetic aperture radar interferogram captured the eastern part of a large-scale frontal structure of daytime midlatitude Es which spans over 250 km in the east-northeast to west-southwest direction. Fine structures are characterized by frontal and disc-shaped patches which are elongated in the same direction as the large-scale frontal structure. Length and width of the disc-shaped patches are 10-20 km and 5-10 km, respectively, and they are quasi-periodically located with a typical separation of 10-15 km. The Kelvin-Helmholtz instability with the vertical shear of zonal winds is considered to be the most likely candidate for the generation mechanism of the frontal patch and disc-shaped patches aligned in the zonal direction.

    @Article{maedaSuzukiFuruyaHekiGRL2016IonophereGNSSandSARsporadicEthroughTEC,
    author = {Maeda, Jun and Suzuki, Takato and Furuya, Masato and Heki, Kosuke},
    title = {Imaging the midlatitude sporadic E plasma patches with a coordinated observation of spaceborne InSAR and GPS total electron content},
    journal = {Geophysical Research Letters},
    year = {2016},
    volume = {43},
    number = {4},
    pages = {1419-1425},
    abstract = {Kilometer-scale fine structures of midlatitude sporadic E (Es) plasma patches have been directly imaged for the first time by an interferogram derived from L band Advanced Land Observation Satellite/Phased Array-type L band Synthetic Aperture Radar data obtained over southwestern Japan. The synthetic aperture radar interferogram captured the eastern part of a large-scale frontal structure of daytime midlatitude Es which spans over 250 km in the east-northeast to west-southwest direction. Fine structures are characterized by frontal and disc-shaped patches which are elongated in the same direction as the large-scale frontal structure. Length and width of the disc-shaped patches are 10-20 km and 5-10 km, respectively, and they are quasi-periodically located with a typical separation of 10-15 km. The Kelvin-Helmholtz instability with the vertical shear of zonal winds is considered to be the most likely candidate for the generation mechanism of the frontal patch and disc-shaped patches aligned in the zonal direction.},
    doi = {10.1002/2015GL067585},
    eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015GL067585},
    file = {:maedaSuzukiFuruyaHekiGRL2016IonophereGNSSandSARsporadicEthroughTEC.pdf:PDF},
    keywords = {sporadic E, GPS, total electron content, synthetic aperture radar, Kelvin-Helmholtz instability},
    owner = {ofrey},
    url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2015GL067585},
    
    }
    


  16. Christophe Magnard, Max Frioud, David Small, Thorsten Brehm, and Erich Meier. Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(3):1072-1085, March 2016. Keyword(s): SAR Processing, SAR Interferometry, InSAR, Multibaseline Interferometry, Ka-band, Airborne SAR, Single-pass Multibaseline Interferometry, airborne radar, image texture, maximum likelihood estimation, millimetre wave radar, motion compensation, phase estimation, radar imaging, radar interferometry, synthetic aperture radar, C2F algorithm, ML method, airborne multibaseline SAR interferometry, calibration steps, coarse-to-fine algorithm, cross-track multibaseline synthetic aperture radar interferometric data, experimental Ka-band multibaseline system, homogeneous texture, imperfect motion compensation, maximum likelihood phase estimation method, noise level, Antenna measurements, Antennas, Calibration, Maximum likelihood estimation, Motion compensation, Phase estimation, Synthetic aperture radar, Interferometry, Ka-band, maximum likelihood (ML), millimeter wave radar, millimeterwave experimental multifrequency polarimetric high-resolution interferometric system (MEMPHIS), multibaseline, phase unwrapping, synthetic aperture radar (SAR).
    Abstract: It has been shown using simulated data that phase estimation of cross-track multibaseline synthetic aperture radar (SAR) interferometric data was most efficiently achieved through a maximum likelihood (ML) method. In this paper, we apply and assess the ML approach on real data, acquired with an experimental Ka-band multibaseline system. Compared to simulated data, dealing with real data implies that several calibration steps be carried out to ensure that the data fit the model. A processing chain was, therefore, designed, including steps responsible for compensating for imperfections observed in the data, such as beam elevation angle dependent phase errors or phase errors caused by imperfect motion compensation. The performance of the ML phase estimation was evaluated by comparing it to results based on a coarse-to-fine (C2F) algorithm, where information from the shorter baselines was used only to unwrap the phase from the longest available baseline. For this purpose, flat areas with high coherence and homogeneous texture were selected in the acquired data. The results show that with only four looks, the noise level was marginally better with the C2F approach and contained fewer outliers. However, with more looks, the ML method consistently delivered better results: noise variance with the C2F approach was slightly but steadily larger than the variance obtained with ML method.

    @Article{magnardFrioudSmallBrehmMeierJSTARS2016MaxLikelihoodPhaseEstimationMBINSAR,
    author = {Christophe Magnard and Max Frioud and David Small and Thorsten Brehm and Erich Meier},
    title = {Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2016},
    volume = {9},
    number = {3},
    pages = {1072-1085},
    month = mar,
    issn = {1939-1404},
    abstract = {It has been shown using simulated data that phase estimation of cross-track multibaseline synthetic aperture radar (SAR) interferometric data was most efficiently achieved through a maximum likelihood (ML) method. In this paper, we apply and assess the ML approach on real data, acquired with an experimental Ka-band multibaseline system. Compared to simulated data, dealing with real data implies that several calibration steps be carried out to ensure that the data fit the model. A processing chain was, therefore, designed, including steps responsible for compensating for imperfections observed in the data, such as beam elevation angle dependent phase errors or phase errors caused by imperfect motion compensation. The performance of the ML phase estimation was evaluated by comparing it to results based on a coarse-to-fine (C2F) algorithm, where information from the shorter baselines was used only to unwrap the phase from the longest available baseline. For this purpose, flat areas with high coherence and homogeneous texture were selected in the acquired data. The results show that with only four looks, the noise level was marginally better with the C2F approach and contained fewer outliers. However, with more looks, the ML method consistently delivered better results: noise variance with the C2F approach was slightly but steadily larger than the variance obtained with ML method.},
    doi = {10.1109/JSTARS.2015.2487685},
    file = {:magnardFrioudSmallBrehmMeierJSTARS2016MaxLikelihoodPhaseEstimationMBINSAR.pdf:PDF},
    keywords = {SAR Processing, SAR Interferometry, InSAR, Multibaseline Interferometry, Ka-band, Airborne SAR, Single-pass Multibaseline Interferometry,airborne radar;image texture;maximum likelihood estimation;millimetre wave radar;motion compensation;phase estimation;radar imaging;radar interferometry;synthetic aperture radar;C2F algorithm;ML method;airborne multibaseline SAR interferometry;calibration steps;coarse-to-fine algorithm;cross-track multibaseline synthetic aperture radar interferometric data;experimental Ka-band multibaseline system;homogeneous texture;imperfect motion compensation;maximum likelihood phase estimation method;noise level;Antenna measurements;Antennas;Calibration;Maximum likelihood estimation;Motion compensation;Phase estimation;Synthetic aperture radar;Interferometry;Ka-band;maximum likelihood (ML);millimeter wave radar;millimeterwave experimental multifrequency polarimetric high-resolution interferometric system (MEMPHIS);multibaseline;phase unwrapping;synthetic aperture radar (SAR)},
    owner = {ofrey},
    pdf = {../../../docs/magnardFrioudSmallBrehmMeierJSTARS2016MaxLikelihoodPhaseEstimationMBINSAR.pdf},
    
    }
    


  17. T. M. Marston and J. L. Kennedy. Volumetric Acoustic Imaging via Circular Multipass Aperture Synthesis. IEEE_J_OE, 41(4):852-867, October 2016. Keyword(s): autonomous underwater vehicles, compressed sensing, matrix algebra, sonar, synthetic aperture radar, AUV, CSAS, analogous synthetic aperture radar tomography, autonomous underwater vehicle, compressive-sensing-based approach, data-driven technique, high-resolution volumetric images, joint sparsity assumption, multidimensional array, multipass circular synthetic aperture sonar, sensing matrices, standard joint sparse solving algorithm, volumetric acoustic imaging, Compressed sensing, Synthetic aperture radar, Synthetic aperture sonar, Tomography, Underwater vehicles, Compressive sensing, multipass sonar, synthetic aperture sonar (SAS), tomography, volumetric imaging.
    @Article{Marston2016b,
    author = {T. M. Marston and J. L. Kennedy},
    title = {Volumetric Acoustic Imaging via Circular Multipass Aperture Synthesis},
    journal = IEEE_J_OE,
    year = {2016},
    volume = {41},
    number = {4},
    month = oct,
    pages = {852--867},
    issn = {0364-9059},
    doi = {10.1109/JOE.2015.2502664},
    keywords = {autonomous underwater vehicles, compressed sensing, matrix algebra, sonar, synthetic aperture radar, AUV, CSAS, analogous synthetic aperture radar tomography, autonomous underwater vehicle, compressive-sensing-based approach, data-driven technique, high-resolution volumetric images, joint sparsity assumption, multidimensional array, multipass circular synthetic aperture sonar, sensing matrices, standard joint sparse solving algorithm, volumetric acoustic imaging, Compressed sensing, Synthetic aperture radar, Synthetic aperture sonar, Tomography, Underwater vehicles, Compressive sensing, multipass sonar, synthetic aperture sonar (SAS), tomography, volumetric imaging},
    owner = {ofrey},
    
    }
    


  18. Timothy M. Marston and Jermaine L. Kennedy. Volumetric Acoustic Imaging via Circular Multipass Aperture Synthesis. IEEE Journal of Oceanic Engineering, PP(99):1-16, 2016. Keyword(s): SAR Processing, SAR Tomography, SAS Tomography, Synthetic Aperture Sonar, SAS, Synthetic Aperture Radar, Circular SAR, Circular SAS, Apertures, Arrays, Navigation, Synthetic aperture radar, Synthetic aperture sonar, Tomography, Compressive sensing, multipass sonar, synthetic aperture sonar (SAS), tomography, volumetric imaging.
    Abstract: In this paper, volumetric imaging via multipass circular synthetic aperture sonar (CSAS) is demonstrated using an autonomous underwater vehicle (AUV). A multidimensional aperture is synthesized by performing a series of circular scans at varying grazing angles around targets and coherently combining the backscattering information from the set of scans to form high-resolution volumetric images. A data-driven technique for precision alignment of the individual scans comprising the multipass set enables synthesis of a multidimensional array. To beamform in the vertical dimension using the irregular and undersampled multipass aperture, a compressive-sensing-based approach is adopted which is similar to methods used in analogous synthetic aperture radar tomography applications but modified to accommodate for the wider fractional bandwidth of the synthetic aperture sonar (SAS) system. The modification exploits a joint sparsity assumption in the vertical scattering profile at different subbands and adapts a standard joint sparse solving algorithm to the relevant case in which the sparsity profile is common between solution vectors but the sensing matrices are different. Results are shown for a variety of targets, including proud and obliquely buried unexploded ordnance, a 2-1 solid aluminum cylinder, and a steel oil drum.

    @Article{marstonKennedyJOE2016CircularTomoSAS,
    author = {Timothy M. Marston and Jermaine L. Kennedy},
    title = {Volumetric Acoustic Imaging via Circular Multipass Aperture Synthesis},
    journal = {IEEE Journal of Oceanic Engineering},
    year = {2016},
    volume = {PP},
    number = {99},
    pages = {1-16},
    issn = {0364-9059},
    abstract = {In this paper, volumetric imaging via multipass circular synthetic aperture sonar (CSAS) is demonstrated using an autonomous underwater vehicle (AUV). A multidimensional aperture is synthesized by performing a series of circular scans at varying grazing angles around targets and coherently combining the backscattering information from the set of scans to form high-resolution volumetric images. A data-driven technique for precision alignment of the individual scans comprising the multipass set enables synthesis of a multidimensional array. To beamform in the vertical dimension using the irregular and undersampled multipass aperture, a compressive-sensing-based approach is adopted which is similar to methods used in analogous synthetic aperture radar tomography applications but modified to accommodate for the wider fractional bandwidth of the synthetic aperture sonar (SAS) system. The modification exploits a joint sparsity assumption in the vertical scattering profile at different subbands and adapts a standard joint sparse solving algorithm to the relevant case in which the sparsity profile is common between solution vectors but the sensing matrices are different. Results are shown for a variety of targets, including proud and obliquely buried unexploded ordnance, a 2-1 solid aluminum cylinder, and a steel oil drum.},
    doi = {10.1109/JOE.2015.2502664},
    file = {:marstonKennedyJOE2016CircularTomoSAS.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, SAS Tomography, Synthetic Aperture Sonar, SAS, Synthetic Aperture Radar, Circular SAR, Circular SAS, Apertures;Arrays;Navigation;Synthetic aperture radar;Synthetic aperture sonar;Tomography;Compressive sensing;multipass sonar;synthetic aperture sonar (SAS);tomography;volumetric imaging},
    owner = {ofrey},
    
    }
    


  19. T. G. Michael, B. Marchand, J. D. Tucker, T. M. Marston, D. D. Sternlicht, and M. R. Azimi-Sadjadi. Image-Based Automated Change Detection for Synthetic Aperture Sonar by Multistage Coregistration and Canonical Correlation Analysis. IEEE_J_OE, 41(3):592-612, July 2016. Keyword(s): backscatter, image registration, sonar imaging, synthetic aperture sonar, transforms, backscattered signals, canonical correlation analysis, image-based automated change detection, multistage coregistration, scale-invariant feature transform algorithm, scene coherence, synthetic aperture sonar, Change detection algorithms, Coherence, Correlation, Navigation, Surges, Synthetic aperture sonar, Automated change detection, canonical correlation analysis (CCA), coherent change detection, coregistration, synthetic aperture sonar (SAS).
    @Article{G-Michael2016,
    author = {Michael, T. G. and Marchand, B. and Tucker, J. D. and Marston, T. M. and Sternlicht, D. D. and Azimi-Sadjadi, M. R.},
    title = {Image-Based Automated Change Detection for Synthetic Aperture Sonar by Multistage Coregistration and Canonical Correlation Analysis},
    journal = IEEE_J_OE,
    year = {2016},
    volume = {41},
    number = {3},
    month = jul,
    pages = {592--612},
    issn = {0364-9059},
    doi = {10.1109/JOE.2015.2465631},
    keywords = {backscatter, image registration, sonar imaging, synthetic aperture sonar, transforms, backscattered signals, canonical correlation analysis, image-based automated change detection, multistage coregistration, scale-invariant feature transform algorithm, scene coherence, synthetic aperture sonar, Change detection algorithms, Coherence, Correlation, Navigation, Surges, Synthetic aperture sonar, Automated change detection, canonical correlation analysis (CCA), coherent change detection, coregistration, synthetic aperture sonar (SAS)},
    owner = {ofrey},
    
    }
    


  20. J. Pan, M. Durand, M. Sandells, J. Lemmetyinen, E. J. Kim, J. Pulliainen, A. Kontu, and C. Derksen. Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation. IEEE Transactions on Geoscience and Remote Sensing, 54(4):2001-2019, April 2016. Keyword(s): radiative transfer, remote sensing, snow, HUT snow emission model, Helsinki University of Technology, brightness temperature simulation, snow water equivalent retrieval algorithm, passive microwave measurement, multiple-layer HUT model, Microwave Emission Model of Layered Snowpacks, scattered intensity, radiative transfer equation, one-flux equation, two-flux theory, HUT scattering coefficient, trapped-radiation, natural snow cover, Sodankyla, Finland, Churchill, Canada, Colorado, USA, snow grain size was, deep snow, Born approximation, root-mean-square error, Snow, Mathematical model, Scattering, Grain size, Microwave theory and techniques, Ice, Correlation, Model comparison, passive microwave remote sensing, snow, Model comparison, passive microwave remote sensing, snow.
    Abstract: Microwave emission models are a critical component of snow water equivalent retrieval algorithms applied to passive microwave measurements. Several such emission models exist, but their differences need to be systematically compared. This paper compares the basic theories of two models: the multiple-layer Helsinki University of Technology (HUT) model and the microwave emission model of layered snowpacks (MEMLS). By comparing the mathematical formulation side by side, three major differences were identified: 1) by assuming that the scattered intensity is mostly (96%) in the forward direction, the HUT model simplifies the radiative transfer equation in 4pi space into two one-flux equations, whereas MEMLS uses a two-flux theory; 2) the HUT scattering coefficient is much larger than the one of MEMLS; and 3) MEMLS considers the trapped radiation inside snow due to internal reflection by a six-flux model, which is not included in HUT. Simulation experiments indicate that the large scattering coefficient of the HUT model compensates for its large forward scattering ratio to some extent, but the effects of one-flux simplification and the trapped radiation still result in different TB simulations between the HUT model and MEMLS. The models were compared with observations of natural snow cover at Sodankyl�, Finland; Churchill, Canada; and Colorado, USA. No optimization of the snow grain size was performed. It shows that the HUT model tends to underestimate TB for deep snow. MEMLS with the physically based improved Born approximation performed best among the models, with a bias of -1.4 K and a root-mean-square error of 11.0 K.

    @Article{panDurandSandellsLemmetyinenKimPulliainenKontuDerksenTGRS2016DifferenceOfHUTandMEMLSandEffectsOnBrightnessTempSim,
    author = {J. {Pan} and M. {Durand} and M. {Sandells} and J. {Lemmetyinen} and E. J. {Kim} and J. {Pulliainen} and A. {Kontu} and C. {Derksen}},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {Differences Between the {HUT} Snow Emission Model and {MEMLS} and Their Effects on Brightness Temperature Simulation},
    year = {2016},
    issn = {1558-0644},
    month = {April},
    number = {4},
    pages = {2001-2019},
    volume = {54},
    abstract = {Microwave emission models are a critical component of snow water equivalent retrieval algorithms applied to passive microwave measurements. Several such emission models exist, but their differences need to be systematically compared. This paper compares the basic theories of two models: the multiple-layer Helsinki University of Technology (HUT) model and the microwave emission model of layered snowpacks (MEMLS). By comparing the mathematical formulation side by side, three major differences were identified: 1) by assuming that the scattered intensity is mostly (96%) in the forward direction, the HUT model simplifies the radiative transfer equation in 4pi space into two one-flux equations, whereas MEMLS uses a two-flux theory; 2) the HUT scattering coefficient is much larger than the one of MEMLS; and 3) MEMLS considers the trapped radiation inside snow due to internal reflection by a six-flux model, which is not included in HUT. Simulation experiments indicate that the large scattering coefficient of the HUT model compensates for its large forward scattering ratio to some extent, but the effects of one-flux simplification and the trapped radiation still result in different TB simulations between the HUT model and MEMLS. The models were compared with observations of natural snow cover at Sodankyl�, Finland; Churchill, Canada; and Colorado, USA. No optimization of the snow grain size was performed. It shows that the HUT model tends to underestimate TB for deep snow. MEMLS with the physically based improved Born approximation performed best among the models, with a bias of -1.4 K and a root-mean-square error of 11.0 K.},
    doi = {10.1109/TGRS.2015.2493505},
    keywords = {radiative transfer;remote sensing;snow;HUT snow emission model;Helsinki University of Technology;brightness temperature simulation;snow water equivalent retrieval algorithm;passive microwave measurement;multiple-layer HUT model;Microwave Emission Model of Layered Snowpacks;scattered intensity;radiative transfer equation;one-flux equation;two-flux theory;HUT scattering coefficient;trapped-radiation;natural snow cover;Sodankyla;Finland;Churchill;Canada;Colorado;USA;snow grain size was;deep snow;Born approximation;root-mean-square error;Snow;Mathematical model;Scattering;Grain size;Microwave theory and techniques;Ice;Correlation;Model comparison;passive microwave remote sensing;snow;Model comparison;passive microwave remote sensing;snow},
    owner = {ofrey},
    
    }
    


  21. M. Pieraccini and L. Miccinesi. ArcSAR for detecting target elevation. Electronics Letters, 52(18):1559-1561, 2016. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, data acquisition, object detection, radar antennas, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, ArcSAR, digital elevation model generation, interferometric differential radar, rotating arm, spatial diversity, synthetic aperture radar, target elevation detection.
    Abstract: ArcSAR is a Synthetic Aperture Radar which recently has been receiving increasing interest in scientific literature. It operates exploiting the spatial diversity of the data acquired by an antenna fixed to a rotating arm. Its great advantage is its capability to synthesise images at 360 deg with constant resolution in azimuth. The ArcSAR, in addition to operate as interferometric differential radar, can detect the elevation of the targets, i.e. it is potentially able to generate digital elevation models of the surrounding field of view.

    @Article{pieracciniMiccinesiEL2016ArcSAR,
    author = {M. Pieraccini and L. Miccinesi},
    title = {{ArcSAR} for detecting target elevation},
    journal = {Electronics Letters},
    year = {2016},
    volume = {52},
    number = {18},
    pages = {1559-1561},
    issn = {0013-5194},
    doi = {10.1049/el.2016.2367},
    abstract = {ArcSAR is a Synthetic Aperture Radar which recently has been receiving increasing interest in scientific literature. It operates exploiting the spatial diversity of the data acquired by an antenna fixed to a rotating arm. Its great advantage is its capability to synthesise images at 360 deg with constant resolution in azimuth. The ArcSAR, in addition to operate as interferometric differential radar, can detect the elevation of the targets, i.e. it is potentially able to generate digital elevation models of the surrounding field of view.},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,data acquisition;object detection;radar antennas;radar imaging;radar interferometry;remote sensing by radar;synthetic aperture radar;ArcSAR;digital elevation model generation;interferometric differential radar;rotating arm;spatial diversity;synthetic aperture radar;target elevation detection},
    owner = {ofrey},
    
    }
    


  22. Octavio Ponce, Pau Prats-Iraola, Rolf Scheiber, Andreas Reigber, and Alberto Moreira. First Airborne Demonstration of Holographic SAR Tomography With Fully Polarimetric Multicircular Acquisitions at L-Band. IEEE_J_GRS, 54(10):6170-6196, October 2016. Keyword(s): geophysical techniques, radar imaging, remote sensing by radar, synthetic aperture radar, 2-D synthetic aperture, Fully Polarimetric Multicircular Acquisitions, German Aerospace Center, Germany, HoloSAR tomogram polarimetric analysis, Kaufbeuren, L-Band, SAR systems, airborne F-SAR sensor, coherent imaging approach, complex reflectivity, compressive sensing, fast-factorized back-projection, forest backscattering analysis, full 3-D reconstructions, generalized likelihood ratio test, geometric acquisition, geoscience community, holographic SAR tomography, holographic techniques, impulse response function, incoherent imaging, individual circular trajectories, internal structure imaging, multicircular SAR acquisitions, polarimetric L-band HoloSAR survey, radar resolution capability function, scatterer polarimetric signature, semitransparent media, sidelobe power, spatial resolution, synthetic aperture radar, target 3-D IRF, tomographic techniques, volumetric backscattering, Apertures, Radar imaging, Spatial resolution, Synthetic aperture radar, Tomography, Circular synthetic aperture radar (CSAR), compressive sensing (CS), fast-factorized back-projection (FFBP), holographic sar tomography (HoloSAR), phase gradient autofocus (PGA), polarimetric synthetic aperture radar (PolSAR).
    @Article{poncePratsScheiberReigberMoreiraTGRS2016HolographicSARTOMOLBand,
    author = {Octavio Ponce and Pau Prats-Iraola and Rolf Scheiber and Andreas Reigber and Alberto Moreira},
    title = {First Airborne Demonstration of Holographic {SAR} Tomography With Fully Polarimetric Multicircular Acquisitions at L-Band},
    journal = IEEE_J_GRS,
    year = {2016},
    volume = {54},
    number = {10},
    month = oct,
    pages = {6170--6196},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2016.2582959},
    keywords = {geophysical techniques, radar imaging, remote sensing by radar, synthetic aperture radar, 2-D synthetic aperture, Fully Polarimetric Multicircular Acquisitions, German Aerospace Center, Germany, HoloSAR tomogram polarimetric analysis, Kaufbeuren, L-Band, SAR systems, airborne F-SAR sensor, coherent imaging approach, complex reflectivity, compressive sensing, fast-factorized back-projection, forest backscattering analysis, full 3-D reconstructions, generalized likelihood ratio test, geometric acquisition, geoscience community, holographic SAR tomography, holographic techniques, impulse response function, incoherent imaging, individual circular trajectories, internal structure imaging, multicircular SAR acquisitions, polarimetric L-band HoloSAR survey, radar resolution capability function, scatterer polarimetric signature, semitransparent media, sidelobe power, spatial resolution, synthetic aperture radar, target 3-D IRF, tomographic techniques, volumetric backscattering, Apertures, Radar imaging, Spatial resolution, Synthetic aperture radar, Tomography, Circular synthetic aperture radar (CSAR), compressive sensing (CS), fast-factorized back-projection (FFBP), holographic sar tomography (HoloSAR), phase gradient autofocus (PGA), polarimetric synthetic aperture radar (PolSAR)},
    owner = {ofrey},
    
    }
    


  23. Martin Proksch, Nick Rutter, Charles Fierz, and Martin Schneebeli. Intercomparison of snow density measurements: bias, precision, and vertical resolution. The Cryosphere, 10(1):371-384, 2016. Keyword(s): Snow characterisation, snow density, density cutter, snow density retrieval, comparison of methods.
    Abstract: Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography ($\mu$CT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between $\mu$CT and gravimetric methods (density cutters) was 5 to 9 %, with a bias of -5 to 2 %, expressed as percentage of the mean $\mu$CT density. In the field, density cutters overestimate (1 to 6 %) densities below and underestimate (1 to 6 %) densities above a threshold between 296 to 350 kg m^-3, dependent on cutter type. Using the mean density per layer of all measurement methods applied in the field ($\mu$CT, box, wedge, and cylinder cutters) and ignoring ice layers, the variation between the methods was 2 to 5 % with a bias of -1 to 1 %. In general, our result suggests that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably. In particular, the millimeter-scale density variations revealed by the high-resolution $\mu$CT contrasted the thick layers with sharp boundaries introduced by the observer. In this respect, the unresolved variation, i.e., the density variation within a layer which is lost by lower resolution sampling or layer aggregation, is critical when snow density measurements are used in numerical simulations.

    @Article{prokschRutterFierzSchneebeliCryosphere2016ComparisonSnowDensityMeasurements,
    author = {Proksch, Martin and Rutter, Nick and Fierz, Charles and Schneebeli, Martin},
    title = {Intercomparison of snow density measurements: bias, precision, and vertical resolution},
    journal = {The Cryosphere},
    year = {2016},
    volume = {10},
    number = {1},
    pages = {371--384},
    abstract = {Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography ($\mu$CT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between $\mu$CT and gravimetric methods (density cutters) was 5 to 9 %, with a bias of -5 to 2 %, expressed as percentage of the mean $\mu$CT density. In the field, density cutters overestimate (1 to 6 %) densities below and underestimate (1 to 6 %) densities above a threshold between 296 to 350 kg m^-3, dependent on cutter type. Using the mean density per layer of all measurement methods applied in the field ($\mu$CT, box, wedge, and cylinder cutters) and ignoring ice layers, the variation between the methods was 2 to 5 % with a bias of -1 to 1 %. In general, our result suggests that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably. In particular, the millimeter-scale density variations revealed by the high-resolution $\mu$CT contrasted the thick layers with sharp boundaries introduced by the observer. In this respect, the unresolved variation, i.e., the density variation within a layer which is lost by lower resolution sampling or layer aggregation, is critical when snow density measurements are used in numerical simulations.},
    doi = {10.5194/tc-10-371-2016},
    file = {:prokschRutterFierzSchneebeliCryosphere2016ComparisonSnowDensityMeasurements.pdf:PDF},
    keywords = {Snow characterisation, snow density, density cutter, snow density retrieval, comparison of methods},
    owner = {ofrey},
    pdf = {../../../docs/prokschRutterFierzSchneebeliCryosphere2016ComparisonSnowDensityMeasurements.pdf},
    url = {https://www.the-cryosphere.net/10/371/2016/},
    
    }
    


  24. A. Recchia, Andrea Monti Guarnieri, Antonio Broquetas, and Antonio Leanza. Impact of Scene Decorrelation on Geosynchronous SAR Data Focusing. IEEE Transactions on Geoscience and Remote Sensing, 54(3):1635-1646, March 2016. Keyword(s): SAR Processing, SAR focusing, autofocus, atmospheric phase, atmospheric phase screen, APS, decorrelation, temporal decorrelation, geostationary, geosynchronous, radar clutter, radar resolution, synthetic aperture radar, Billingsley intrinsic clutter motion model, GEOSAR signal-to-clutter ratio, azimuth resolution, clutter energy, geosynchronous SAR data focusing, ground based radar experiment, power spectral density, scene decorrelation, two-way propagation losses, Azimuth, Clutter, Decorrelation, Focusing, Synthetic aperture radar, Thyristors, Focusing, Geosynchronous Synthetic Aperture Radar (GEOSAR), scene decorrelation, wind-blown clutter.
    Abstract: We discuss the effects of the clutter on geosynchronous SAR systems exploiting long integration times (from minutes to hours) to counteract for two-way propagation losses and increase azimuth resolution. Only stable targets will be correctly focused whereas unstable targets will spread their energy along azimuth direction. We derive here a generic model for the spreading of the clutter energy based on the power spectral density of the clutter itself. We then assume the Billingsley Intrinsic Clutter Motion model, representing the clutter power spectrum as an exponential decay, and derive the expected GEOSAR signal-to-clutter ratio. We also provide some results from a Ground Based RADAR experiment aimed at assessing the long-term clutter statistics for different scenarios to complement the Internal Clutter Motion model, mainly derived for windblown trees. Finally, we discuss the expected performances of two GEOSAR systems with different acquisition geometries.

    @Article{recchiaMontiGuarnieriBroquetasLeanzaTGRS2016DecorrelationInGeosynchronousSARFocusing,
    author = {Recchia, A. and Monti Guarnieri, Andrea and Broquetas, Antonio and Leanza, Antonio},
    title = {Impact of Scene Decorrelation on Geosynchronous {SAR} Data Focusing},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2016},
    volume = {54},
    number = {3},
    month = {March},
    pages = {1635-1646},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2015.2486385},
    abstract = {We discuss the effects of the clutter on geosynchronous SAR systems exploiting long integration times (from minutes to hours) to counteract for two-way propagation losses and increase azimuth resolution. Only stable targets will be correctly focused whereas unstable targets will spread their energy along azimuth direction. We derive here a generic model for the spreading of the clutter energy based on the power spectral density of the clutter itself. We then assume the Billingsley Intrinsic Clutter Motion model, representing the clutter power spectrum as an exponential decay, and derive the expected GEOSAR signal-to-clutter ratio. We also provide some results from a Ground Based RADAR experiment aimed at assessing the long-term clutter statistics for different scenarios to complement the Internal Clutter Motion model, mainly derived for windblown trees. Finally, we discuss the expected performances of two GEOSAR systems with different acquisition geometries.},
    keywords = {SAR Processing, SAR focusing, autofocus, atmospheric phase, atmospheric phase screen, APS, decorrelation, temporal decorrelation, geostationary, geosynchronous, radar clutter;radar resolution;synthetic aperture radar;Billingsley intrinsic clutter motion model;GEOSAR signal-to-clutter ratio;azimuth resolution;clutter energy;geosynchronous SAR data focusing;ground based radar experiment;power spectral density;scene decorrelation;two-way propagation losses;Azimuth;Clutter;Decorrelation;Focusing;Synthetic aperture radar;Thyristors;Focusing;Geosynchronous Synthetic Aperture Radar (GEOSAR);scene decorrelation;wind-blown clutter},
    owner = {ofrey},
    
    }
    


  25. Jamal Saeedi and Karim Faez. A back-projection autofocus algorithm based on flight trajectory optimization for synthetic aperture radar imaging. Multidimensional Systems and Signal Processing, 27(2):411, April 2016.
    Abstract: In this paper, a new autofocus algorithm is presented for back-projection (BP) image formation of synthetic aperture radar (SAR) imaging. The approach is based on maximizing a cost function obtained by prominent points in different sub-apertures of constructed SAR image by varying the flight trajectory parameters. While image-quality-based autofocus approach together with BP algorithm can be computationally intensive, we use approximations that allow optimal corrections to be derived. The approach is applicable for focusing different signal processing algorithms by obtaining modified flight trajectory parameters. Different examples demonstrate the effectiveness of the new autofocus approach applied to the frequency modulated continuous wave mode SAR dataset.

    @Article{Saeedi2016,
    author = {Saeedi, Jamal and Faez, Karim},
    title = {A back-projection autofocus algorithm based on flight trajectory optimization for synthetic aperture radar imaging},
    year = {2016},
    date = {2016-04-01},
    volume = {27},
    number = {2},
    month = apr,
    pages = {411},
    issn = {1573-0824},
    doi = {10.1007/s11045-014-0308-1},
    url = {http://dx.doi.org/10.1007/s11045-014-0308-1},
    abstract = {In this paper, a new autofocus algorithm is presented for back-projection (BP) image formation of synthetic aperture radar (SAR) imaging. The approach is based on maximizing a cost function obtained by prominent points in different sub-apertures of constructed SAR image by varying the flight trajectory parameters. While image-quality-based autofocus approach together with BP algorithm can be computationally intensive, we use approximations that allow optimal corrections to be derived. The approach is applicable for focusing different signal processing algorithms by obtaining modified flight trajectory parameters. Different examples demonstrate the effectiveness of the new autofocus approach applied to the frequency modulated continuous wave mode SAR dataset.},
    journal = {Multidimensional Systems and Signal Processing},
    owner = {ofrey},
    publisher = {Springer},
    
    }
    


  26. Muhammad Adnan Siddique, Urs Wegmuller, Irena Hajnsek, and Othmar Frey. Single-look SAR tomography as an add-on to PSI for improved deformation analysis in urban areas. IEEE Trans. Geosci. Remote Sens., 54(10):6119-6137, 2016. Keyword(s): SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, TerraSAR-X, Barcelona, interferometric stacking.
    Abstract: Persistent scatterer interferometry (PSI) is in operational use for spaceborne SAR-based deformation analysis. A limitation inherently associated with PSI is that by definition a persistent scatterer (PS) is a single dominant scatterer. Therefore, pixels containing signal contributions from multiple scatterers, as in the case of a layover, are typically rejected in the PSI processing, which in turn limits deformation retrieval. SAR tomography has the ability to resolve layovers. This paper investigates the value-addition that can be achieved by operationally combining SAR tomography with a PSI approach towards the objective of improving deformation sampling in layover-affected urban areas. Different tomographic phase models are implemented and compared as regards their suitability in resolving layovers. Single-look beamforming-based tomographic inversion and a generalized likelihood ratio (GLRT)-based detection strategy are used to detect single and double scatterers. The quantity of the detected scatterers is weighed against their quality as defined in terms of the phase deviation between the SLC measurements and the tomographic model fit. The gain in deformation sampling that can be derived with tomography relative to a PSI-based analysis is quantitatively assessed, and alongside the quality of the scatterers obtained with tomography is compared with the quality of the PSs identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap images. The results obtained show that, although there is a trade-off between the quantity and the quality of the detected scatterers, the tested SAR tomography approach leads to an improvement in deformation sampling in layover-affected areas.

    @Article{siddiqueWegmullerHajnsekFreyTGRS2016TOMOBarca,
    author = {Siddique, Muhammad Adnan and Wegmuller, Urs and Hajnsek, Irena and Frey, Othmar},
    title = {Single-look {SAR} tomography as an add-on to {PSI} for improved deformation analysis in urban areas},
    journal = {{IEEE} Trans. Geosci. Remote Sens.},
    year = {2016},
    volume = {54},
    number = {10},
    pages = {6119-6137},
    issn = {0196-2892},
    abstract = {Persistent scatterer interferometry (PSI) is in operational use for spaceborne SAR-based deformation analysis. A limitation inherently associated with PSI is that by definition a persistent scatterer (PS) is a single dominant scatterer. Therefore, pixels containing signal contributions from multiple scatterers, as in the case of a layover, are typically rejected in the PSI processing, which in turn limits deformation retrieval. SAR tomography has the ability to resolve layovers. This paper investigates the value-addition that can be achieved by operationally combining SAR tomography with a PSI approach towards the objective of improving deformation sampling in layover-affected urban areas. Different tomographic phase models are implemented and compared as regards their suitability in resolving layovers. Single-look beamforming-based tomographic inversion and a generalized likelihood ratio (GLRT)-based detection strategy are used to detect single and double scatterers. The quantity of the detected scatterers is weighed against their quality as defined in terms of the phase deviation between the SLC measurements and the tomographic model fit. The gain in deformation sampling that can be derived with tomography relative to a PSI-based analysis is quantitatively assessed, and alongside the quality of the scatterers obtained with tomography is compared with the quality of the PSs identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap images. The results obtained show that, although there is a trade-off between the quantity and the quality of the detected scatterers, the tested SAR tomography approach leads to an improvement in deformation sampling in layover-affected areas.},
    doi = {10.1109/TGRS.2016.2581261},
    file = {:siddiqueWegmullerHajnsekFreyTGRS2016TOMOBarca.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, TerraSAR-X, Barcelona, interferometric stacking},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWegmullerHajnsekFreyTGRS2016TOMOBarca.pdf},
    url = {http://ieeexplore.ieee.org/document/7508450},
    
    }
    


  27. Xiaoshen Song and Weidong Yu. Processing video-SAR data with the fast backprojection method. IEEE Transactions on Aerospace and Electronic Systems, 52(6):2838-2848, December 2016. Keyword(s): SAR Processing, Back-Projection, Time-Domain Back-Projection, TDBP, Fast-Factorized Back-Projection, FFBP, radar imaging, synthetic aperture radar, FBP algorithm, GR, Gotcha data set, O(N2 log N) complexity reduction, ROI, X-band SAR measurement, fast backprojection method, general region, image sequence, land-imaging mode, recursive procedure, region of interest, synthetic aperture radar, video framing, video-SAR data processing, video-SAR image formation, Apertures, Azimuth, Complexity theory, Image resolution, Radar imaging, Synthetic aperture radar, Time-domain analysis.
    Abstract: Video synthetic aperture radar (video-SAR) is a land-imaging mode where a sequence of images is continuously formed when the radar platform either flies by or circles the scene. In this paper, the fast backprojection (FBP) algorithm is introduced for video-SAR image formation. It avoids unnecessary duplication of processing for the overlapping parts between consecutive video frames and achieves O(N2 log N) complexity through a recursive procedure. To reduce the processing complexity in video-SAR system, the scene is partitioned into the general region (GR) and the region of interest (ROI). In different regions, different aperture lengths are used. The proposed method allows a direct trade between processing speed and focused quality for the GR, meanwhile reserving particular details in the ROI. The effectiveness is validated both for a simulated scene and for X-band SAR measurements from the Gotcha data set.

    @Article{songYuTAES2016VideoSARBackprojection,
    author = {Song, Xiaoshen and Yu, Weidong},
    title = {Processing video-{SAR} data with the fast backprojection method},
    journal = {IEEE Transactions on Aerospace and Electronic Systems},
    year = {2016},
    volume = {52},
    number = {6},
    pages = {2838-2848},
    month = dec,
    issn = {0018-9251},
    abstract = {Video synthetic aperture radar (video-SAR) is a land-imaging mode where a sequence of images is continuously formed when the radar platform either flies by or circles the scene. In this paper, the fast backprojection (FBP) algorithm is introduced for video-SAR image formation. It avoids unnecessary duplication of processing for the overlapping parts between consecutive video frames and achieves O(N2 log N) complexity through a recursive procedure. To reduce the processing complexity in video-SAR system, the scene is partitioned into the general region (GR) and the region of interest (ROI). In different regions, different aperture lengths are used. The proposed method allows a direct trade between processing speed and focused quality for the GR, meanwhile reserving particular details in the ROI. The effectiveness is validated both for a simulated scene and for X-band SAR measurements from the Gotcha data set.},
    doi = {10.1109/TAES.2016.150581},
    file = {:songYuTAES2016VideoSARBackprojection.pdf:PDF},
    keywords = {SAR Processing, Back-Projection, Time-Domain Back-Projection, TDBP, Fast-Factorized Back-Projection, FFBP,radar imaging;synthetic aperture radar;FBP algorithm;GR;Gotcha data set;O(N2 log N) complexity reduction;ROI;X-band SAR measurement;fast backprojection method;general region;image sequence;land-imaging mode;recursive procedure;region of interest;synthetic aperture radar;video framing;video-SAR data processing;video-SAR image formation;Apertures;Azimuth;Complexity theory;Image resolution;Radar imaging;Synthetic aperture radar;Time-domain analysis},
    owner = {ofrey},
    pdf = {../../../docs/songYuTAES2016VideoSARBackprojection.pdf},
    
    }
    


  28. S. Tebaldini, F. Rocca, M. Mariotti d'Alessandro, and L. Ferro-Famil. Phase Calibration of Airborne Tomographic SAR Data via Phase Center Double Localization. IEEE Trans. Geosci. Remote Sens., 54(3):1775-1792, March 2016. Keyword(s): SAR Processing, SAR tomography, Apertures, Calibration, Focusing, Sensors, Surfaces, Synthetic aperture radar, Tomography, Distributed media, phase calibration, reconstruction algorithms, synthetic aperture radar (SAR), tomography.
    Abstract: Synthetic aperture radar (SAR) data collected over a 2-D synthetic aperture can be processed to focus the illuminated scatterers in the 3-D space, using a number of signal processing techniques generally grouped under the name of SAR tomography (TomoSAR). A fundamental requirement for TomoSAR processing is to have precise knowledge of the platform position along the 2-D synthetic aperture. This requirement is not easily met in the case where the 2-D aperture is formed by collecting different flight lines (i.e., 1-D apertures) in a repeat-pass fashion, which is the typical case of airborne and spaceborne TomoSAR. Subwavelength platform position errors give rise to residual phase screens among different passes, which hinder coherent focusing in the 3-D space. In this paper, we propose a strategy for calibrating repeat-pass tomographic SAR data that allows us to accurately estimate and remove such residual phase screens in the absence of reference targets and prior information about terrain topography and even in the absence of any point- or surface-like target within the illuminated scene. The problem is tackled by observing that multiple flight lines provide enough information to jointly estimate platform and target positions, up to a roto-translation of the coordinate system used for representing the imaged scene. The employment of volumetric scatterers in the calibration process is enabled by the phase linking algorithm, which allows us to represent them as equivalent phase centers. The proposed approach is demonstrated through numerical simulations, in order to validate the results based on the exact knowledge of the simulated scatterers, and using real data from the ESA campaigns AlpTomoSAR, BioSAR 2008, and TropiSAR. A cross-check of the results from simultaneous P- and L-band acquisitions from the TropiSAR data set indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters.

    @Article{tebaldiniRoccaMariottiFerroFamilTGRS2015PhaseCalibrationTomoSAR,
    author = {Tebaldini, S. and Rocca, F. and Mariotti d'Alessandro, M. and Ferro-Famil, L.},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    title = {Phase Calibration of Airborne Tomographic {SAR} Data via Phase Center Double Localization},
    year = {2016},
    issn = {0196-2892},
    month = {mar},
    number = {3},
    pages = {1775--1792},
    volume = {54},
    abstract = {Synthetic aperture radar (SAR) data collected over a 2-D synthetic aperture can be processed to focus the illuminated scatterers in the 3-D space, using a number of signal processing techniques generally grouped under the name of SAR tomography (TomoSAR). A fundamental requirement for TomoSAR processing is to have precise knowledge of the platform position along the 2-D synthetic aperture. This requirement is not easily met in the case where the 2-D aperture is formed by collecting different flight lines (i.e., 1-D apertures) in a repeat-pass fashion, which is the typical case of airborne and spaceborne TomoSAR. Subwavelength platform position errors give rise to residual phase screens among different passes, which hinder coherent focusing in the 3-D space. In this paper, we propose a strategy for calibrating repeat-pass tomographic SAR data that allows us to accurately estimate and remove such residual phase screens in the absence of reference targets and prior information about terrain topography and even in the absence of any point- or surface-like target within the illuminated scene. The problem is tackled by observing that multiple flight lines provide enough information to jointly estimate platform and target positions, up to a roto-translation of the coordinate system used for representing the imaged scene. The employment of volumetric scatterers in the calibration process is enabled by the phase linking algorithm, which allows us to represent them as equivalent phase centers. The proposed approach is demonstrated through numerical simulations, in order to validate the results based on the exact knowledge of the simulated scatterers, and using real data from the ESA campaigns AlpTomoSAR, BioSAR 2008, and TropiSAR. A cross-check of the results from simultaneous P- and L-band acquisitions from the TropiSAR data set indicates that the dispersion of the retrieved flight trajectories is limited to a few millimeters.},
    doi = {10.1109/TGRS.2015.2488358},
    file = {:tebaldiniRoccaMariottiFerroFamilTGRS2015PhaseCalibrationTomoSAR.pdf:PDF},
    keywords = {SAR Processing, SAR tomography, Apertures;Calibration;Focusing;Sensors;Surfaces;Synthetic aperture radar;Tomography;Distributed media;phase calibration;reconstruction algorithms;synthetic aperture radar (SAR);tomography},
    pdf = {../../../docs/tebaldiniRoccaMariottiFerroFamilTGRS2015PhaseCalibrationTomoSAR.pdf},
    publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
    
    }
    


  29. Jan Torgrimsson, Patrik Dammert, Hans Hellsten, and Lars M. H. Ulander. An Efficient Solution to the Factorized Geometrical Autofocus Problem. IEEE Transactions on Geoscience and Remote Sensing, 54(8):4732-4748, August 2016. Keyword(s): SAR Processing, Autofocus, Fast-Factorized Back-Projection, FFBP, radar imaging, synthetic aperture radar, 6-D autofocus problem, FGA algorithm, adjustable geometry parameters, factorized back-projection formulation, factorized geometrical autofocus problem, geometrical variation, global autofocus solution, magnitude values, maximizing focus quality, peak-to-sidelobe ratio, point-like targets, synthetic-aperture-radar processing, ultrawideband CARABAS II data, Apertures, Geometry, Radar imaging, Radar tracking, Search problems, Synthetic aperture radar, Autofocus, back-projection, synthetic aperture radar (SAR).
    Abstract: This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data.

    @Article{torgrimssonDammertHellstenUlanderTGRS2016FFBPEfficientAutofocus,
    author = {Jan Torgrimsson and Patrik Dammert and Hans Hellsten and Lars M. H. Ulander},
    title = {An Efficient Solution to the Factorized Geometrical Autofocus Problem},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2016},
    volume = {54},
    number = {8},
    pages = {4732-4748},
    month = aug,
    issn = {0196-2892},
    abstract = {This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data.},
    doi = {10.1109/TGRS.2016.2550663},
    file = {:torgrimssonDammertHellstenUlanderTGRS2016FFBPEfficientAutofocus.pdf:PDF},
    keywords = {SAR Processing, Autofocus, Fast-Factorized Back-Projection, FFBP, radar imaging;synthetic aperture radar;6-D autofocus problem;FGA algorithm;adjustable geometry parameters;factorized back-projection formulation;factorized geometrical autofocus problem;geometrical variation;global autofocus solution;magnitude values;maximizing focus quality;peak-to-sidelobe ratio;point-like targets;synthetic-aperture-radar processing;ultrawideband CARABAS II data;Apertures;Geometry;Radar imaging;Radar tracking;Search problems;Synthetic aperture radar;Autofocus;back-projection;synthetic aperture radar (SAR)},
    
    }
    


  30. Luigi Tosi, Cristina Da Lio, Tazio Strozzi, and Pietro Teatini. Combining L- and X-Band SAR Interferometry to Assess Ground Displacements in Heterogeneous Coastal Environments: The Po River Delta and Venice Lagoon, Italy. Remote Sensing, 8(4):308, 2016.
    Abstract: From leveling to SAR-based interferometry, the monitoring of land subsidence in coastal transitional environments significantly improved. However, the simultaneous assessment of the ground movements in these peculiar environments is still challenging. This is due to the presence of relatively small built-up zones and infrastructures, e.g., coastal infrastructures, bridges, and river embankments, within large natural or rural lands, e.g., river deltas, lagoons, and farmland. In this paper we present a multi-band SAR methodology to integrate COSMO-SkyMed and ALOS-PALSAR images. The method consists of a proper combination of the very high-resolution X-band Persistent Scatterer Interferometry (PSI), which achieves high-density and precise measurements on single structures and constructed areas, with L-band Short-Baseline SAR Interferometry (SBAS), properly implemented to raise its effectiveness in retrieving information in vegetated and wet zones. The combined methodology is applied on the Po River Delta and Venice coastland, Northern Italy, using 16 ALOS-PALSAR and 31 COSMO-SkyMed images covering the period between 2007 and 2011. After a proper calibration of the single PSI and SBAS solution using available GPS records, the datasets have been combined at both the regional and local scales. The measured displacements range from ~0 mm/yr down to 35 mm/yr. The results reveal the variable pattern of the subsidence characterizing the more natural and rural environments without losing the accuracy in quantifying the sinking of urban areas and infrastructures. Moreover, they allow improving the interpretation of the natural and anthropogenic processes responsible for the ongoing subsidence.

    @Article{tosiDaLioStrozziTeatiniRemoteSensing2016SubsidenceVeniceLbandXband,
    author = {Tosi, Luigi and Da Lio, Cristina and Strozzi, Tazio and Teatini, Pietro},
    title = {Combining {L-} and {X-}Band {SAR} Interferometry to Assess Ground Displacements in Heterogeneous Coastal Environments: The {Po} River Delta and {Venice} Lagoon, {Italy}},
    journal = {Remote Sensing},
    year = {2016},
    volume = {8},
    number = {4},
    pages = {308},
    issn = {2072-4292},
    abstract = {From leveling to SAR-based interferometry, the monitoring of land subsidence in coastal transitional environments significantly improved. However, the simultaneous assessment of the ground movements in these peculiar environments is still challenging. This is due to the presence of relatively small built-up zones and infrastructures, e.g., coastal infrastructures, bridges, and river embankments, within large natural or rural lands, e.g., river deltas, lagoons, and farmland. In this paper we present a multi-band SAR methodology to integrate COSMO-SkyMed and ALOS-PALSAR images. The method consists of a proper combination of the very high-resolution X-band Persistent Scatterer Interferometry (PSI), which achieves high-density and precise measurements on single structures and constructed areas, with L-band Short-Baseline SAR Interferometry (SBAS), properly implemented to raise its effectiveness in retrieving information in vegetated and wet zones. The combined methodology is applied on the Po River Delta and Venice coastland, Northern Italy, using 16 ALOS-PALSAR and 31 COSMO-SkyMed images covering the period between 2007 and 2011. After a proper calibration of the single PSI and SBAS solution using available GPS records, the datasets have been combined at both the regional and local scales. The measured displacements range from ~0 mm/yr down to 35 mm/yr. The results reveal the variable pattern of the subsidence characterizing the more natural and rural environments without losing the accuracy in quantifying the sinking of urban areas and infrastructures. Moreover, they allow improving the interpretation of the natural and anthropogenic processes responsible for the ongoing subsidence.},
    doi = {10.3390/rs8040308},
    file = {:tosiDaLioStrozziTeatiniRemoteSensing2016SubsidenceVeniceLbandXband.pdf:PDF},
    owner = {ofrey},
    pdf = {../../../docs/tosiDaLioStrozziTeatiniRemoteSensing2016SubsidenceVeniceLbandXband.pdf},
    url = {http://www.mdpi.com/2072-4292/8/4/308},
    
    }
    


  31. Andr Twele, Wenxi Cao, Simon Plank, and Sandro Martinis. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37(13):2990-3004, 2016. Keyword(s): Sentinel-1, Flood Mapping.
    Abstract: This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0\% and 96.1\% and Cohen's kappa coefficients (kappa) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.

    @Article{tweleCaoPlankMartinisIJRS2016Sentinel1FloodMapping,
    author = {Andr\'e Twele and Wenxi Cao and Simon Plank and Sandro Martinis},
    journal = {International Journal of Remote Sensing},
    title = {Sentinel-1-based flood mapping: a fully automated processing chain},
    year = {2016},
    number = {13},
    pages = {2990-3004},
    volume = {37},
    abstract = {This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0\% and 96.1\% and Cohen's kappa coefficients (kappa) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.},
    doi = {10.1080/01431161.2016.1192304},
    eprint = {https://doi.org/10.1080/01431161.2016.1192304},
    keywords = {Sentinel-1, Flood Mapping},
    publisher = {Taylor Francis},
    url = {https://doi.org/10.1080/01431161.2016.1192304},
    
    }
    


  32. Viet Thuy Vu and Mats I. Pettersson. Fast Backprojection Algorithms Based on Subapertures and Local Polar Coordinates for General Bistatic Airborne SAR Systems. IEEE Trans. Geosci. Remote Sens., 54(5):2706-2712, May 2016. Keyword(s): SAR Processing, Back-Projection, Fast Back-Projection, Fast-Factorized Back-Projection, Azimuth Focusing, airborne radar, synthetic aperture radar, bistatic CARABAS-like data, fast backprojection algorithms, general bistatic airborne SAR systems, half-power beamwidths, image quality measurements, interpolation step, local polar coordinates, peak sidelobe ratio, subapertures, Image reconstruction, Receivers, Signal processing algorithms, Synthetic aperture radar, Time-domain analysis, Transmitters, Algorithm, bistatic, fast backprojection, polar coordinates, synthetic aperture radar (SAR).
    Abstract: This paper introduces a bistatic fast backprojection synthetic aperture radar (SAR) algorithm that is available for different bistatic geometries. The proposed algorithm is tested with the bistatic CARABAS-like data, and the results indicate that the algorithm is a good candidate for bistatic SAR data processing. The image quality measurements are quite similar to the referenced values obtained with the bistatic global backprojection algorithm. That is, the peak sidelobe ratio (PSLR) is -13.7 dB in comparison to the referenced PSLR of -13.8 dB. The half-power beamwidths (HPBWs) measured on the cuts in x and y and the direction where the peak sidelobes locate are 2.8, 3.7, and 3.5 m, respectively, which are approximate to the referenced HPBWs. The small differences in the measured results mainly come from the interpolation step of the algorithm.

    @Article{vuPetterssonTGRS2016FastBackprojectionBistatic,
    author = {Vu, Viet Thuy and Pettersson, Mats I.},
    title = {Fast Backprojection Algorithms Based on Subapertures and Local Polar Coordinates for General Bistatic Airborne {SAR} Systems},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2016},
    volume = {54},
    number = {5},
    pages = {2706-2712},
    month = may,
    issn = {0196-2892},
    abstract = {This paper introduces a bistatic fast backprojection synthetic aperture radar (SAR) algorithm that is available for different bistatic geometries. The proposed algorithm is tested with the bistatic CARABAS-like data, and the results indicate that the algorithm is a good candidate for bistatic SAR data processing. The image quality measurements are quite similar to the referenced values obtained with the bistatic global backprojection algorithm. That is, the peak sidelobe ratio (PSLR) is -13.7 dB in comparison to the referenced PSLR of -13.8 dB. The half-power beamwidths (HPBWs) measured on the cuts in x and y and the direction where the peak sidelobes locate are 2.8, 3.7, and 3.5 m, respectively, which are approximate to the referenced HPBWs. The small differences in the measured results mainly come from the interpolation step of the algorithm.},
    doi = {10.1109/TGRS.2015.2504787},
    file = {:vuPetterssonTGRS2016FastBackprojectionBistatic.pdf:PDF},
    keywords = {SAR Processing, Back-Projection, Fast Back-Projection, Fast-Factorized Back-Projection, Azimuth Focusing, airborne radar;synthetic aperture radar;bistatic CARABAS-like data;fast backprojection algorithms;general bistatic airborne SAR systems;half-power beamwidths;image quality measurements;interpolation step;local polar coordinates;peak sidelobe ratio;subapertures;Image reconstruction;Receivers;Signal processing algorithms;Synthetic aperture radar;Time-domain analysis;Transmitters;Algorithm;bistatic;fast backprojection;polar coordinates;synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  33. Urs Wegmuller, Charles L. Werner, Tazio Strozzi, Andreas Wiesmann, Othmar Frey, and Maurizio Santoro. Sentinel-1 Support in the GAMMA Software. Procedia Computer Science, 100:1305-1312, 2016. Keyword(s): SAR Processing, Sentinel-1, Interferometry, SAR Interferometry, InSAR, persistent scatterer interferometry, PSI, offset tracking, split-beam interferometry, GAMMA Software.
    Abstract: First results using the new Sentinel-1 SAR look very promising but the special interferometric wide-swath data acquired in the TOPS mode makes InSAR processing more challenging than for normal stripmap mode data. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful book-keeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR, PSI and offset tracking work.

    @Article{WegmullerEtAlProcediaSentinel1GammaSoftware,
    author = {Wegmuller, Urs and Werner, Charles L. and Strozzi, Tazio and Wiesmann, Andreas and Frey, Othmar and Santoro, Maurizio},
    title = {Sentinel-1 Support in the {GAMMA} Software},
    journal = {Procedia Computer Science},
    year = {2016},
    volume = {100},
    pages = {1305-1312},
    issn = {1877-0509},
    abstract = {First results using the new Sentinel-1 SAR look very promising but the special interferometric wide-swath data acquired in the TOPS mode makes InSAR processing more challenging than for normal stripmap mode data. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful book-keeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR, PSI and offset tracking work.},
    doi = {http://dx.doi.org/10.1016/j.procs.2016.09.246},
    file = {:WegmullerEtAlProcediaSentinel1GammaSoftware.pdf:PDF},
    keywords = {SAR Processing, Sentinel-1, Interferometry, SAR Interferometry, InSAR, persistent scatterer interferometry, PSI, offset tracking, split-beam interferometry, GAMMA Software},
    owner = {ofrey},
    url = {http://www.sciencedirect.com/science/article/pii/S1877050916324152},
    
    }
    


  34. S. Zwieback and I. Hajnsek. Influence of Vegetation Growth on the Polarimetric Zero-Baseline DInSAR Phase Diversity ---Implications for Deformation Studies. IEEE_J_GRS, 54(5):3070-3082, May 2016. Keyword(s): crops, geophysical techniques, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, L-band zero-baseline data set, agricultural crop, barley, crop type, deformation study, differential SAR interferometry, displacement estimation, growing season, in situ observed biomass, maize, polarimetric DInSAR phase diversity, polarimetric coherence region, polarization diversity, sugar beet, synthetic aperture radar, vegetation canopy, vegetation effect, vegetation growth effect, wheat, zero-baseline DInSAR phase diversity, Coherence, Interferometry, Synthetic aperture radar, Systematics, Vegetation, Vegetation mapping, Birefringence, radar interferometry, radar remote sensing, synthetic aperture radar, vegetation.
    @Article{Zwieback2016a,
    author = {S. Zwieback and I. Hajnsek},
    title = {Influence of Vegetation Growth on the Polarimetric Zero-Baseline DInSAR Phase Diversity ---Implications for Deformation Studies},
    year = {2016},
    volume = {54},
    number = {5},
    month = may,
    pages = {3070--3082},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2015.2511118},
    journal = IEEE_J_GRS,
    keywords = {crops, geophysical techniques, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, L-band zero-baseline data set, agricultural crop, barley, crop type, deformation study, differential SAR interferometry, displacement estimation, growing season, in situ observed biomass, maize, polarimetric DInSAR phase diversity, polarimetric coherence region, polarization diversity, sugar beet, synthetic aperture radar, vegetation canopy, vegetation effect, vegetation growth effect, wheat, zero-baseline DInSAR phase diversity, Coherence, Interferometry, Synthetic aperture radar, Systematics, Vegetation, Vegetation mapping, Birefringence, radar interferometry, radar remote sensing, synthetic aperture radar, vegetation},
    owner = {ofrey},
    
    }
    


  35. S. Zwieback, X. Liu, S. Antonova, B. Heim, A. Bartsch, J. Boike, and I. Hajnsek. A Statistical Test of Phase Closure to Detect Influences on DInSAR Deformation Estimates Besides Displacements and Decorrelation Noise: Two Case Studies in High-Latitude Regions. IEEE_J_GRS, 54(9):5588-5601, September 2016. Keyword(s): atmospheric precipitation, displacement measurement, geophysical techniques, radar interferometry, remote sensing by radar, snow, statistical analysis, synthetic aperture radar, DInSAR deformation estimates, Finland, Ku-band, Lena Delta, Russia, Sodankyl, X-band observations, decorrelation noise, differential interferometric synthetic aperture radar, displacement measurement, high-latitude regions, ice-rich permafrost regions, phase measurement, snow metamorphism, statistical test, summer precipitation event, Decorrelation, Optical interferometry, Scattering, Snow, Synthetic aperture radar, Displacement measurement, interferometry, phase measurement, remote sensing, snow, soil, statistics, synthetic aperture radar.
    @Article{Zwieback2016,
    author = {S. Zwieback and X. Liu and S. Antonova and B. Heim and A. Bartsch and J. Boike and I. Hajnsek},
    title = {A Statistical Test of Phase Closure to Detect Influences on DInSAR Deformation Estimates Besides Displacements and Decorrelation Noise: Two Case Studies in High-Latitude Regions},
    year = {2016},
    volume = {54},
    number = {9},
    month = sep,
    pages = {5588--5601},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2016.2569435},
    journal = IEEE_J_GRS,
    keywords = {atmospheric precipitation, displacement measurement, geophysical techniques, radar interferometry, remote sensing by radar, snow, statistical analysis, synthetic aperture radar, DInSAR deformation estimates, Finland, Ku-band, Lena Delta, Russia, Sodankyl{\"{a}}, X-band observations, decorrelation noise, differential interferometric synthetic aperture radar, displacement measurement, high-latitude regions, ice-rich permafrost regions, phase measurement, snow metamorphism, statistical test, summer precipitation event, Decorrelation, Optical interferometry, Scattering, Snow, Synthetic aperture radar, Displacement measurement, interferometry, phase measurement, remote sensing, snow, soil, statistics, synthetic aperture radar},
    owner = {ofrey},
    
    }
    


Conference articles

  1. Simone Baffelli, Othmar Frey, Charles L. Werner, and Irena Hajnsek. System Characterization and Polarimetric Calibration of the Ku-Band Advanced Polarimetric Interferometer. In Proc. of EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar, pages 735-740, June 2016. Keyword(s): Terrestrial Radar Interferometry, TRI, Ground-based radar, Interferometry, Polarimetry, Calibration, Pol-GPRI.
    Abstract: This paper addresses the system characterization and the polarimetric calibration of the Ku-Band Advanced Polarimetric Interferometer (KAPRI). KAPRI is an FMCW ground-based real aperture radar system that uses slotted waveguide antennas. The rotation of the antennas introduces undesired phase ramps in azimuth. We present a geometrical model to account for this phase, and propose a method to correct it. Experimental data with a set of trihedral corner reflectors (TCR) in the scene was acquired with the system. A linear phase variation of 30 degrees was observed over the TCR which was geometrically modeled and successfully corrected.

    @InProceedings{baffelliFreyWernerHajnsekEUSAR2016PolGPRI,
    author = {Simone Baffelli and Othmar Frey and Charles L. Werner and Irena Hajnsek},
    title = {System Characterization and Polarimetric Calibration of the {Ku}-Band Advanced Polarimetric Interferometer},
    booktitle = {Proc. of EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar},
    year = {2016},
    pages = {735-740},
    month = jun,
    abstract = {This paper addresses the system characterization and the polarimetric calibration of the Ku-Band Advanced Polarimetric Interferometer (KAPRI). KAPRI is an FMCW ground-based real aperture radar system that uses slotted waveguide antennas. The rotation of the antennas introduces undesired phase ramps in azimuth. We present a geometrical model to account for this phase, and propose a method to correct it. Experimental data with a set of trihedral corner reflectors (TCR) in the scene was acquired with the system. A linear phase variation of 30 degrees was observed over the TCR which was geometrically modeled and successfully corrected.},
    file = {:baffelliFreyWernerHajnsekEUSAR2016PolGPRI.pdf:PDF},
    keywords = {Terrestrial Radar Interferometry, TRI, Ground-based radar, Interferometry, Polarimetry, Calibration, Pol-GPRI},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/baffelliFreyWernerHajnsekEUSAR2016PolGPRI.pdf},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7559403},
    
    }
    


  2. T. J. Czernuszewicz, J. W. Homeister, M. C. Caughey, B. Y. Huang, E. R. Lee, C.A. Zamora, M. A. Farber, J. J. Fulton, P. F. Ford, W. A. Marston, R. Vallabhaneni, T. C. Nichols, and C. M. Gallippi. Carotid plaque characterization with ARFI imaging: Blinded reader study. In Proc. IEEE Int. Ultrasonics Symp., pages 1-4, September 2016. Keyword(s): acoustic imaging, biomedical ultrasonics, blood vessels, calcium, feature extraction, medical image processing, proteins, regression analysis, sensitivity analysis, ARFI Imaging, AUC, CEA, acoustic radiation force impulse imaging, area under the ROC curve, blinded reader study, calcium, carotid endarterectomy, carotid plaque characterization, carotid vasculature, collagen, fibrous cap thickness measurements, histologic examination, intraplaque hemorrhage, linear regression, necrotic core, noninvasive elastography imaging technique, parametric 2D ARFI images, peak displacement, plaque feature detection, plaque risk assessment, receiver operating characteristic curve analysis, surgery, thromboembolic events, vulnerable atherosclerotic plaque, Acoustics, Atherosclerosis, Calcium, Hemorrhaging, Imaging, In vivo, Thickness measurement, ARFI, CEA, acoustic radiation force, atherosclerosis, carotid endarterectomy, plaque characterization, stroke.
    @InProceedings{Czernuszewicz2016,
    author = {T. J. Czernuszewicz and J. W. Homeister and M. C. Caughey and B. Y. Huang and E. R. Lee and Zamora, C.A. and M. A. Farber and J. J. Fulton and P. F. Ford and W. A. Marston and R. Vallabhaneni and T. C. Nichols and C. M. Gallippi},
    title = {Carotid plaque characterization with {ARFI} imaging: Blinded reader study},
    booktitle = {Proc. IEEE Int. Ultrasonics Symp.},
    year = {2016},
    month = sep,
    pages = {1-4},
    doi = {10.1109/ULTSYM.2016.7728873},
    keywords = {acoustic imaging, biomedical ultrasonics, blood vessels, calcium, feature extraction, medical image processing, proteins, regression analysis, sensitivity analysis, ARFI Imaging, AUC, CEA, acoustic radiation force impulse imaging, area under the ROC curve, blinded reader study, calcium, carotid endarterectomy, carotid plaque characterization, carotid vasculature, collagen, fibrous cap thickness measurements, histologic examination, intraplaque hemorrhage, linear regression, necrotic core, noninvasive elastography imaging technique, parametric 2D ARFI images, peak displacement, plaque feature detection, plaque risk assessment, receiver operating characteristic curve analysis, surgery, thromboembolic events, vulnerable atherosclerotic plaque, Acoustics, Atherosclerosis, Calcium, Hemorrhaging, Imaging, In vivo, Thickness measurement, ARFI, CEA, acoustic radiation force, atherosclerosis, carotid endarterectomy, plaque characterization, stroke},
    owner = {ofrey},
    
    }
    


  3. Othmar Frey, Charles L. Werner, Rafael Caduff, and Andreas Wiesmann. A time series of SAR tomographic profiles of a snowpack. In Proc. of EUSAR 2016, pages 726-730, June 2016. Keyword(s): SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band, Polarimetry, ground-based radar, Snow, Snowpack, geophysical signal processing, radar polarimetry, synthetic aperture radar.
    Abstract: Recently, the SnowScat hardware - a tower-mounted fully-polarimetric scatterometer at X-/Ku-band - has been enhanced to also provide a tomographic profiling mode which allows to obtain high-resolution 2-D vertical profiles that may provide further insights into the electromagnetic interaction within layered snowpacks. In winter 2014/2015, a first test campaign was carried out yielding a successful proof of concept of the hardware, tomographic measurement, and basic processing concept. As a follow-up, in Nov/Dec 2015, the SnowScat device was installed at a test site on 1700m altitude close to the Grimsel pass in Switzerland. Since then it has been acquiring a time series of tomographic profiles of a snow pack. In this paper, we present and discuss first results of this new time series.

    @InProceedings{freyWernerCaduffWiesmannEUSAR2016SnowScatTomo,
    author = {Othmar Frey and Charles L. Werner and Rafael Caduff and Andreas Wiesmann},
    title = {A time series of {SAR} tomographic profiles of a snowpack},
    booktitle = {Proc. of EUSAR 2016},
    year = {2016},
    pages = {726-730},
    month = jun,
    abstract = {Recently, the SnowScat hardware - a tower-mounted fully-polarimetric scatterometer at X-/Ku-band - has been enhanced to also provide a tomographic profiling mode which allows to obtain high-resolution 2-D vertical profiles that may provide further insights into the electromagnetic interaction within layered snowpacks. In winter 2014/2015, a first test campaign was carried out yielding a successful proof of concept of the hardware, tomographic measurement, and basic processing concept. As a follow-up, in Nov/Dec 2015, the SnowScat device was installed at a test site on 1700m altitude close to the Grimsel pass in Switzerland. Since then it has been acquiring a time series of tomographic profiles of a snow pack. In this paper, we present and discuss first results of this new time series.},
    file = {:freyWernerCaduffWiesmannEUSAR2016SnowScatTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band,Polarimetry, ground-based radar; Snow,Snowpack, geophysical signal processing;radar polarimetry;synthetic aperture radar},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerCaduffWiesmannEUSAR2016SnowScatTomo.pdf},
    url = {http://ieeexplore.ieee.org/document/7559401},
    
    }
    


  4. Othmar Frey, Charles L. Werner, Rafael Caduff, and Andreas Wiesmann. A time series of tomographic profiles of a snow pack measured with SnowScat at X-/Ku-Band. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 1, pages 17-20, July 2016. Keyword(s): SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band, Polarimetry, ground-based radar, Snow, Snowpack, geophysical signal processing, radar polarimetry, synthetic aperture radar.
    Abstract: The SnowScat device is a ground-based stepped-frequency continuous-wave (SFCW) scatterometer supporting fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. It was originally designed to support the investigation and validation of Snow Water Equivalent (SWE) retrieval algorithms in the context of the development of the deselected COld REgions Hydrology High-resolution Observatory (CoReH20) candidate Earth Explorer 7 mission. Recently, the SnowScat hardware has been enhanced to also provide a tomographic profiling mode which allows to obtain high-resolution 2-D vertical profiles that may provide further insight into the electromagnetic interaction within layered snow packs. In winter 2014/2015, a first test campaign was carried out yielding a successful proof of concept of the enhanced hardware, tomographic measurement, and basic processing concept. In Nov/Dec 2015, the SnowScat device was then installed as a part of the SnowLab experiment at a test site on 1700m altitude close to the Grimsel pass in Switzerland. A comprehensive time series of tomographic profiles of a snow pack was acquired until end of March, 2016. In this paper, we present and discuss first results of this new time series of tomographic profiles including 2-D vertical profiles of backscatter, phase difference between the copolar channels, and interferometric phase difference.

    @InProceedings{freyWernerWiesmannIGARSS2016SnowScatTomo,
    author = {Othmar Frey and Charles L. Werner and Rafael Caduff and Andreas Wiesmann},
    title = {A time series of tomographic profiles of a snow pack measured with SnowScat at X-/Ku-Band},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2016},
    volume = {1},
    pages = {17-20},
    month = jul,
    abstract = {The SnowScat device is a ground-based stepped-frequency continuous-wave (SFCW) scatterometer supporting fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. It was originally designed to support the investigation and validation of Snow Water Equivalent (SWE) retrieval algorithms in the context of the development of the deselected COld REgions Hydrology High-resolution Observatory (CoReH20) candidate Earth Explorer 7 mission. Recently, the SnowScat hardware has been enhanced to also provide a tomographic profiling mode which allows to obtain high-resolution 2-D vertical profiles that may provide further insight into the electromagnetic interaction within layered snow packs. In winter 2014/2015, a first test campaign was carried out yielding a successful proof of concept of the enhanced hardware, tomographic measurement, and basic processing concept. In Nov/Dec 2015, the SnowScat device was then installed as a part of the SnowLab experiment at a test site on 1700m altitude close to the Grimsel pass in Switzerland. A comprehensive time series of tomographic profiles of a snow pack was acquired until end of March, 2016. In this paper, we present and discuss first results of this new time series of tomographic profiles including 2-D vertical profiles of backscatter, phase difference between the copolar channels, and interferometric phase difference.},
    doi = {10.1109/IGARSS.2016.7728995},
    file = {:freyWernerWiesmannIGARSS2016SnowScatTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band,Polarimetry, ground-based radar; Snow,Snowpack, geophysical signal processing;radar polarimetry;synthetic aperture radar},
    owner = {ofrey},
    url = {http://ieeexplore.ieee.org/document/7728995},
    
    }
    


  5. G. Gomba, F. De Zan, and A. Parizzi. Ionospheric Phase Screen and Ionospheric Azimuth Shift Estimation Combining the Split-Spectrum and Multi-Squint Methods. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-4, June 2016. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, ionospheric electromagnetic wave propagation, synthetic aperture radar, L-band interferograms, L-band synthetic aperture radar interferometric pairs, SAR interferograms, advanced land observing satellite phased-array, differential ionospheric path delay, geophysical processes, ground deformation signals, ionospheric effects operational compensation, ionospheric phase, split-spectrum method, tropospheric path delay, Accuracy, Azimuth, Coherence, Delays, Estimation, Ionosphere, Synthetic aperture radar, Interferometric synthetic aperture radar (InSAR), ionosphere estimation, split spectrum, synthetic aperture radar (SAR) ionospheric effects.
    @InProceedings{Gomba2016,
    author = {G. Gomba and F. De Zan and A. Parizzi},
    title = {Ionospheric Phase Screen and Ionospheric Azimuth Shift Estimation Combining the Split-Spectrum and Multi-Squint Methods},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    pages = {1--4},
    month = jun,
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry,ionospheric electromagnetic wave propagation, synthetic aperture radar, L-band interferograms, L-band synthetic aperture radar interferometric pairs, SAR interferograms, advanced land observing satellite phased-array, differential ionospheric path delay, geophysical processes, ground deformation signals, ionospheric effects operational compensation, ionospheric phase, split-spectrum method, tropospheric path delay, Accuracy, Azimuth, Coherence, Delays, Estimation, Ionosphere, Synthetic aperture radar, Interferometric synthetic aperture radar (InSAR), ionosphere estimation, split spectrum, synthetic aperture radar (SAR) ionospheric effects},
    owner = {ofrey},
    
    }
    


  6. U. Herter, H. Schmaljohann, and T. Fickenscher. Autofocus performance on multi channel SAS images in the presence of overlapping phase centers. In OCEANS 2016 MTS/IEEE Monterey, pages 1-6, September 2016. Keyword(s): geophysical image processing, image restoration, optical focusing, sonar imaging, synthetic aperture sonar, DPCA, RPC, SPGA focusing, autofocus performance, blurred images, data driven micronavigation, displaced phase center antenna, echo signals, multichannel SAS images, navigation data, overlapping phase centers, raw echo data, redundant phase centers, residual phase errors, side lobe levels, strip-map phase gradient autofocus, synthetic aperture images, synthetic aperture sonar, Apertures, Approximation algorithms, Sonar navigation, Synthetic aperture sonar, Transmitters, aperture sonar, autofocus, multi-channel, strip-map.
    Abstract: Synthetic aperture sonar (SAS) suffers from a fundamental problem: The navigation data accuracy required for coherent summation of the echo signals is not directly achievable. Unamended this issue leads to heavily blurred images. Fortunately, under certain conditions, algorithms like displaced phase center antenna (DPCA) can be used to fine tune the navigation from the raw echo data itself. In contrary to DPCA, strip-map phase gradient autofocus (SPGA) is an algorithm which extracts residual phase errors from processed synthetic aperture images. The results can be used to correct and reprocess the raw data yielding images with reduced blurring. In the presence of overlapping phase centers in raw data, as required for data driven micro navigation like DPCA, some assumptions of SPGA are violated and can cause degradation of it's results. In this paper we investigate the effect of overlapping (redundant) phase centers (RPC) in raw data on the performance of SPGA. Results indicate that the use of redundant data during image formation can bias the phase information in SAS imagery and therefore affects SPGA focusing. In this case, side lobe levels in the focused images are increased compared to images processed without RPCs. Suitable selection schemes should be employed prior to processing to avoid biasing of the phase information due to data collected at redundant phase centers if SPGA processing on top of DPCA is required.

    @InProceedings{7761082,
    author = {U. Herter and H. Schmaljohann and T. Fickenscher},
    title = {Autofocus performance on multi channel {SAS} images in the presence of overlapping phase centers},
    booktitle = {OCEANS 2016 MTS/IEEE Monterey},
    year = {2016},
    pages = {1-6},
    month = sep,
    abstract = {Synthetic aperture sonar (SAS) suffers from a fundamental problem: The navigation data accuracy required for coherent summation of the echo signals is not directly achievable. Unamended this issue leads to heavily blurred images. Fortunately, under certain conditions, algorithms like displaced phase center antenna (DPCA) can be used to fine tune the navigation from the raw echo data itself. In contrary to DPCA, strip-map phase gradient autofocus (SPGA) is an algorithm which extracts residual phase errors from processed synthetic aperture images. The results can be used to correct and reprocess the raw data yielding images with reduced blurring. In the presence of overlapping phase centers in raw data, as required for data driven micro navigation like DPCA, some assumptions of SPGA are violated and can cause degradation of it's results. In this paper we investigate the effect of overlapping (redundant) phase centers (RPC) in raw data on the performance of SPGA. Results indicate that the use of redundant data during image formation can bias the phase information in SAS imagery and therefore affects SPGA focusing. In this case, side lobe levels in the focused images are increased compared to images processed without RPCs. Suitable selection schemes should be employed prior to processing to avoid biasing of the phase information due to data collected at redundant phase centers if SPGA processing on top of DPCA is required.},
    doi = {10.1109/OCEANS.2016.7761082},
    keywords = {geophysical image processing;image restoration;optical focusing;sonar imaging;synthetic aperture sonar;DPCA;RPC;SPGA focusing;autofocus performance;blurred images;data driven micronavigation;displaced phase center antenna;echo signals;multichannel SAS images;navigation data;overlapping phase centers;raw echo data;redundant phase centers;residual phase errors;side lobe levels;strip-map phase gradient autofocus;synthetic aperture images;synthetic aperture sonar;Apertures;Approximation algorithms;Sonar navigation;Synthetic aperture sonar;Transmitters;aperture sonar;autofocus;multi-channel;strip-map},
    owner = {ofrey},
    
    }
    


  7. G. Krieger, T. Rommel, and A. Moreira. MIMO-SAR Tomography. In Proceedings of EUSAR 2016: 11th European Conference on Synthetic Aperture Radar, pages 1-6, June 2016.
    Abstract: MIMO SAR employs multiple transmit and receive channels to improve the imaging performance and to acquire novel geoinformation products. One example is SAR tomography, where the simultaneous transmission and reception with multiple antennas can provide a large number of baselines with a small number of antennas. In the limit, an appropriately designed MIMO-SAR configuration with NTx transmitters and NRx receivers can provide in total NTx . NRx independent phase centers and therefore NTx . NRx - 1 independent baselines for SAR tomography. The other extreme is provided by uniform linear arrays with co-located transmitters and receivers. Such configurations are characterized by a large number of overlapping effective phase centers and are therefore regarded as highly redundant. In this paper, we will show that such a redundancy is nevertheless well suited to resolve an inherent challenge of conventional SAR tomography, which is limited in providing unambiguous 3-D scatterer position estimates in case of multiple scattering. For this, we show that redundant MIMO arrays allow not only an a posteriori beamforming on receive, but, at the same time, also a comparable a posteriori (i.e. after data acquisition) beamforming on transmit. This means that one can emulate, from one and the same recorded MIMO-SAR data set, different illumination scenarios on transmit and receive. By evaluating the 2-D spectrum provided by the independent Tx and Rx beams, it becomes then possible to differentiate between single- and multiplebounce scattering. The separation between single- and double-bounce scattering has also been successfully demonstrated in a ground-based radar experiment and is presented in another EUSAR paper.

    @InProceedings{kriegerRommelMoreiraEUSAR2016MIMOSARTomography,
    author = {G. {Krieger} and T. {Rommel} and A. {Moreira}},
    booktitle = {Proceedings of EUSAR 2016: 11th European Conference on Synthetic Aperture Radar},
    title = {MIMO-SAR Tomography},
    year = {2016},
    month = {June},
    pages = {1-6},
    abstract = {MIMO SAR employs multiple transmit and receive channels to improve the imaging performance and to acquire novel geoinformation products. One example is SAR tomography, where the simultaneous transmission and reception with multiple antennas can provide a large number of baselines with a small number of antennas. In the limit, an appropriately designed MIMO-SAR configuration with NTx transmitters and NRx receivers can provide in total NTx . NRx independent phase centers and therefore NTx . NRx - 1 independent baselines for SAR tomography. The other extreme is provided by uniform linear arrays with co-located transmitters and receivers. Such configurations are characterized by a large number of overlapping effective phase centers and are therefore regarded as highly redundant. In this paper, we will show that such a redundancy is nevertheless well suited to resolve an inherent challenge of conventional SAR tomography, which is limited in providing unambiguous 3-D scatterer position estimates in case of multiple scattering. For this, we show that redundant MIMO arrays allow not only an a posteriori beamforming on receive, but, at the same time, also a comparable a posteriori (i.e. after data acquisition) beamforming on transmit. This means that one can emulate, from one and the same recorded MIMO-SAR data set, different illumination scenarios on transmit and receive. By evaluating the 2-D spectrum provided by the independent Tx and Rx beams, it becomes then possible to differentiate between single- and multiplebounce scattering. The separation between single- and double-bounce scattering has also been successfully demonstrated in a ground-based radar experiment and is presented in another EUSAR paper.},
    owner = {ofrey},
    
    }
    


  8. H. Liao and F. J. Meyer. A combined estimator for Interferometric SAR ionosphere correction. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 6499-6501, July 2016. Keyword(s): Faraday effect, ionospheric techniques, radar interferometry, radar polarimetry, synthetic aperture radar, Faraday rotation based method, InSAR differential ionosphere, InSAR ionospheric effect correction, azimuth shift based method, interferometric SAR ionosphere correction, interferometric synthetic aperture radar ionosphere correction, ionospheric geometric distortion, multiple aperture interferometric azimuth shift, polarimetric property, split spectrum InSAR technique, Earthquakes, Faraday effect, Interferometry, Ionosphere, L-band, Synthetic aperture radar.
    @InProceedings{Liao2016a,
    author = {H. Liao and F. J. Meyer},
    title = {A combined estimator for Interferometric {SAR} ionosphere correction},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2016},
    pages = {6499--6501},
    month = jul,
    doi = {10.1109/IGARSS.2016.7730698},
    keywords = {Faraday effect, ionospheric techniques, radar interferometry, radar polarimetry, synthetic aperture radar, Faraday rotation based method, InSAR differential ionosphere, InSAR ionospheric effect correction, azimuth shift based method, interferometric SAR ionosphere correction, interferometric synthetic aperture radar ionosphere correction, ionospheric geometric distortion, multiple aperture interferometric azimuth shift, polarimetric property, split spectrum InSAR technique, Earthquakes, Faraday effect, Interferometry, Ionosphere, L-band, Synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  9. H. Liao and F. J. Meyer. Ionospheric effect correction of ice motion mapping using interferometric synthetic aperture radar. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 6502-6504, July 2016. Keyword(s): adaptive filters, geophysical signal processing, glaciology, ice, ionosphere, radar interferometry, remote sensing by radar, synthetic aperture radar, AD 1990, Antarctica, C-band ERS1-2, Envisat ASAR, Greenland, InSAR-based ionospheric correction, L-band ALOS 1-2 PALSAR SAR data, Radarsat-1-2, Sentinel-1, X band TerraSAR-X, adaptive filter technique, automatic phase unwrapping error correction, coregistration technique, differential ionospheric phase signal, error correction algorithm, filter-based method, ice mass balance, ice motion analysis, ice motion mapping, ice motion monitoring, ice sheet, ice velocity, interferogram, interferometric synthetic aperture radar, ionospheric effect correction, ionospheric error, ionospheric phase delay, sea level rise, split spectrum technique, Antarctica, Ice, Ionosphere, L-band, Monitoring, Sea level, Synthetic aperture radar.
    @InProceedings{Liao2016,
    author = {H. Liao and F. J. Meyer},
    title = {Ionospheric effect correction of ice motion mapping using interferometric synthetic aperture radar},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2016},
    pages = {6502-6504},
    month = jul,
    doi = {10.1109/IGARSS.2016.7730699},
    keywords = {adaptive filters, geophysical signal processing, glaciology, ice, ionosphere, radar interferometry, remote sensing by radar, synthetic aperture radar, AD 1990, Antarctica, C-band ERS1-2, Envisat ASAR, Greenland, InSAR-based ionospheric correction, L-band ALOS 1-2 PALSAR SAR data, Radarsat-1-2, Sentinel-1, X band TerraSAR-X, adaptive filter technique, automatic phase unwrapping error correction, coregistration technique, differential ionospheric phase signal, error correction algorithm, filter-based method, ice mass balance, ice motion analysis, ice motion mapping, ice motion monitoring, ice sheet, ice velocity, interferogram, interferometric synthetic aperture radar, ionospheric effect correction, ionospheric error, ionospheric phase delay, sea level rise, split spectrum technique, Antarctica, Ice, Ionosphere, L-band, Monitoring, Sea level, Synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  10. P. Lopez-Dekker, F. Q. d. Almeida, M. Rodriguez-Cassola, P. Prats, O. Ponce, and M. Younis. End-to-end simulation of reflector based DBF SAR Systems. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-5, June 2016.
    @InProceedings{Lopez-Dekker2016,
    author = {P. Lopez-Dekker and F. Q. d. Almeida and M. Rodriguez-Cassola and P. Prats and O. Ponce and M. Younis},
    title = {End-to-end simulation of reflector based DBF {SAR} Systems},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    month = jun,
    pages = {1--5},
    owner = {ofrey},
    
    }
    


  11. T. Marston and J. Kennedy. TomoSAS images of acoustically penetrable objects. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-4, June 2016.
    @InProceedings{Marston2016,
    author = {T. Marston and J. Kennedy},
    title = {TomoSAS images of acoustically penetrable objects},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    month = jun,
    pages = {1--4},
    owner = {ofrey},
    
    }
    


  12. T. Marston and J. Kennedy. TomoSAS in bathymetrically complex environments. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-4, June 2016.
    @InProceedings{Marston2016a,
    author = {T. Marston and J. Kennedy},
    title = {TomoSAS in bathymetrically complex environments},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    month = jun,
    pages = {1--4},
    owner = {ofrey},
    
    }
    


  13. A. Moreira, O. Ponce, M. Nannini, M. Pardini, P. Prats, A. Reigber, K. Papathanassiou, and G. Krieger. Multi-baseline spaceborne SAR imaging. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 1420-1423, July 2016. Keyword(s): geophysical image processing, holography, radar imaging, radar interferometry, radar polarimetry, remote sensing by radar, spaceborne radar, synthetic aperture radar, HoloSAR, PolInSAR, TomoSAR, across-track interferometry, along- track interferometry, glacier movement, ground deformation, holography SAR, multi-baseline imaging capability, multi-dimensional data space, multibaseline spaceborne SAR imaging, multistatic SAR configuration, ocean current, polarimetric SAR interferometry, spaceborne SAR development, spaceborne SAR image product, sparse array, surface topography measurement, tomography SAR, Interferometry, Radar imaging, Radar polarimetry, Spaceborne radar, Synthetic aperture radar, Tomography, Multi-Baseline Imaging, Polarimetric SAR Interferometry, Polarimetry, SAR Holography, SAR Tomography, Synthetic Aperture Radar (SAR).
    @InProceedings{Moreira2016,
    author = {A. Moreira and O. Ponce and M. Nannini and M. Pardini and P. Prats and A. Reigber and K. Papathanassiou and G. Krieger},
    title = {Multi-baseline spaceborne {SAR} imaging},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2016},
    month = jul,
    pages = {1420--1423},
    doi = {10.1109/IGARSS.2016.7729363},
    keywords = {geophysical image processing, holography, radar imaging, radar interferometry, radar polarimetry, remote sensing by radar, spaceborne radar, synthetic aperture radar, HoloSAR, PolInSAR, TomoSAR, across-track interferometry, along- track interferometry, glacier movement, ground deformation, holography SAR, multi-baseline imaging capability, multi-dimensional data space, multibaseline spaceborne SAR imaging, multistatic SAR configuration, ocean current, polarimetric SAR interferometry, spaceborne SAR development, spaceborne SAR image product, sparse array, surface topography measurement, tomography SAR, Interferometry, Radar imaging, Radar polarimetry, Spaceborne radar, Synthetic aperture radar, Tomography, Multi-Baseline Imaging, Polarimetric SAR Interferometry, Polarimetry, SAR Holography, SAR Tomography, Synthetic Aperture Radar (SAR)},
    owner = {ofrey},
    
    }
    


  14. Stephan Palm, Rainer Sommer, A. Hommes, Nils Pohl, and Uwe Stilla. Mobile Mapping by FMCW Synthetic Aperture Radar Operating at 300 GHZ. In Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, volume XLI-B1, pages 81-87, June 2016. Copernicus GmbH. Keyword(s): SAR Processing, Miranda, Miranda 300, FMCW, FMCW SAR, Mobile Radar Mapping, Car-borne SAR, Street Mapping, Ultra-High Resolution SAR, Subcentimeter Resolution.
    Abstract: While optical cameras or laser systems are widely used for mobile mapping low attention was payed for radar systems. Due to new semiconductor technologies, compact and leight weight SAR systems based on the Frequency Modulated Continuous Wave (FMCW) principle in the millimeter wave domain can serve for mobile radar mapping on cars. For mapping of long stripes along roads in close range a special strategy for focusing of SAR images was developed. Hereby local adapted planes for processing are used considering the IMU data of the sensor. An experimental system was designed for high resolution radar mapping of urban scenes in close range geometry. This small and leight weighted system has a bandwidth of 30 GHz (5 mm resolution) and operates with 300 GHz in the lower terahertz domain. Experiments with a van in an urban scenario were carried out for proof of applicability of an operating SAR system resolving objects in the subcentimeter domain. The results show that narrow cracks in the asphalt of the road are visible and the measuring of small metallic objects placed in the scene is possible. Based on this mobile mapping techniques a first result from an acquisition of vertical facade structure is shown.

    @InProceedings{palmSommerHommesPohlStillaISPRS2016Miranda300GHzFMCW,
    author = {Stephan Palm and Rainer Sommer and A. Hommes and Nils Pohl and Uwe Stilla},
    booktitle = {Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1},
    title = {Mobile Mapping by {FMCW} Synthetic Aperture Radar Operating at 300 {GHZ}},
    year = {2016},
    month = jun,
    pages = {81-87},
    publisher = {Copernicus {GmbH}},
    volume = {{XLI}-B1},
    abstract = {While optical cameras or laser systems are widely used for mobile mapping low attention was payed for radar systems. Due to new semiconductor technologies, compact and leight weight SAR systems based on the Frequency Modulated Continuous Wave (FMCW) principle in the millimeter wave domain can serve for mobile radar mapping on cars. For mapping of long stripes along roads in close range a special strategy for focusing of SAR images was developed. Hereby local adapted planes for processing are used considering the IMU data of the sensor. An experimental system was designed for high resolution radar mapping of urban scenes in close range geometry. This small and leight weighted system has a bandwidth of 30 GHz (5 mm resolution) and operates with 300 GHz in the lower terahertz domain. Experiments with a van in an urban scenario were carried out for proof of applicability of an operating SAR system resolving objects in the subcentimeter domain. The results show that narrow cracks in the asphalt of the road are visible and the measuring of small metallic objects placed in the scene is possible. Based on this mobile mapping techniques a first result from an acquisition of vertical facade structure is shown.},
    doi = {10.5194/isprs-archives-XLI-B1-81-2016},
    file = {:palmSommerHommesPohlStillaISPRS2016Miranda300GHzFMCW.pdf:PDF},
    journal = {{ISPRS} - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
    keywords = {SAR Processing, Miranda, Miranda 300, FMCW, FMCW SAR, Mobile Radar Mapping, Car-borne SAR, Street Mapping, Ultra-High Resolution SAR, Subcentimeter Resolution},
    owner = {ofrey},
    pdf = {../../../docs/palmSommerHommesPohlStillaISPRS2016Miranda300GHzFMCW.pdf},
    
    }
    


  15. M. Pieraccini. Polarimetrie RotoSAR. In Proc. IEEE Radar Conf. (RadarConf), pages 1-5, May 2016. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, radar antennas, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, ground based inteferometric synthetic aperture radar systems, linear mechanical guide, polarimetric RotoSAR, radar head, radar images, remote sensing instruments, rotating antenna GB-SAR, Monitoring, Radar antennas, Radar imaging, Radar polarimetry, Radar remote sensing, Synthetic aperture radar, GB-SAR, SAR, radar.
    @InProceedings{Pieraccini2016,
    author = {M. Pieraccini},
    title = {Polarimetrie RotoSAR},
    booktitle = {Proc. IEEE Radar Conf. (RadarConf)},
    year = {2016},
    month = may,
    pages = {1--5},
    doi = {10.1109/RADAR.2016.7485186},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,radar antennas, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, ground based inteferometric synthetic aperture radar systems, linear mechanical guide, polarimetric RotoSAR, radar head, radar images, remote sensing instruments, rotating antenna GB-SAR, Monitoring, Radar antennas, Radar imaging, Radar polarimetry, Radar remote sensing, Synthetic aperture radar, GB-SAR, SAR, radar},
    owner = {ofrey},
    
    }
    


  16. O. Ponce, H. Joerg, R. Scheiber, P. Prats, I. Hajnsek, and A. Reigber. First study on holographic SAR tomography over agricultural crops at C-/X-band. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 7403-7406, July 2016. Keyword(s): crops, geophysical image processing, image reconstruction, radar polarimetry, remote sensing by radar, synthetic aperture radar, 2D polarimetric image, 3D crop field backscattering, 3D forest backscattering distribution, 3D imaging reconstruction, 3D polarimetric image, C-band SAR, DLR F-SAR sensor, Germany, HoloSAR campaign, HoloSAR imaging mode, HoloSAR tomography, Wallerfing, X-band SAR, agricultural crop, azimuthal aspect angle, holographic SAR, scattering mechanisms, tomographic constellation, Tomography, Agricultural crops, Fast Factorized Back-Projection (FFBP), Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR).
    @InProceedings{Ponce2016,
    author = {O. Ponce and H. Joerg and R. Scheiber and P. Prats and I. Hajnsek and A. Reigber},
    title = {First study on holographic {SAR} tomography over agricultural crops at C-/X-band},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2016},
    month = jul,
    pages = {7403--7406},
    doi = {10.1109/IGARSS.2016.7730931},
    keywords = {crops, geophysical image processing, image reconstruction, radar polarimetry, remote sensing by radar, synthetic aperture radar, 2D polarimetric image, 3D crop field backscattering, 3D forest backscattering distribution, 3D imaging reconstruction, 3D polarimetric image, C-band SAR, DLR F-SAR sensor, Germany, HoloSAR campaign, HoloSAR imaging mode, HoloSAR tomography, Wallerfing, X-band SAR, agricultural crop, azimuthal aspect angle, holographic SAR, scattering mechanisms, tomographic constellation, Tomography, Agricultural crops, Fast Factorized Back-Projection (FFBP), Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR)},
    owner = {ofrey},
    
    }
    


  17. O. Ponce, R. Scheiber, P. Prats, I. Hajnsek, and A. Reigber. Multi-dimensional airborne holographic SAR tomography reconstruction for glaciers at L-/P-band. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 9-12, July 2016. Keyword(s): geophysical image processing, glaciology, hydrological techniques, image reconstruction, remote sensing by radar, solid modelling, synthetic aperture radar, 2-D image arc-pattern, 2-D image circular pattern, 3-D imaging reconstructions, Greenland, HoIoSAR campaign, HoloSAR mode, K-Transect, circular synthetic aperture, cryosphere, fast factorized back-projection, fully polarimetric data, glacier structures, glacier vertical profile, ice sheet vertical profile, ice structures, multidimensional airborne holographic SAR tomography reconstruction, vertical synthetic aperture, Apertures, Ice, Image resolution, L-band, Synthetic aperture radar, Tomography, Cryosphere, Fast Factorized Back-Projection (FFBP), Glaciers, Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR).
    @InProceedings{Ponce2016a,
    author = {O. Ponce and R. Scheiber and P. Prats and I. Hajnsek and A. Reigber},
    title = {Multi-dimensional airborne holographic {SAR} tomography reconstruction for glaciers at L-/P-band},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2016},
    month = jul,
    pages = {9--12},
    doi = {10.1109/IGARSS.2016.7728993},
    keywords = {geophysical image processing, glaciology, hydrological techniques, image reconstruction, remote sensing by radar, solid modelling, synthetic aperture radar, 2-D image arc-pattern, 2-D image circular pattern, 3-D imaging reconstructions, Greenland, HoIoSAR campaign, HoloSAR mode, K-Transect, circular synthetic aperture, cryosphere, fast factorized back-projection, fully polarimetric data, glacier structures, glacier vertical profile, ice sheet vertical profile, ice structures, multidimensional airborne holographic SAR tomography reconstruction, vertical synthetic aperture, Apertures, Ice, Image resolution, L-band, Synthetic aperture radar, Tomography, Cryosphere, Fast Factorized Back-Projection (FFBP), Glaciers, Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR)},
    owner = {ofrey},
    
    }
    


  18. R. Que, O. Ponce, S. V. Baumgartner, and R. Scheiber. Multi-mode Real-Time SAR On-Board Processing. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-6, June 2016.
    @InProceedings{Que2016,
    author = {R. Que and O. Ponce and S. V. Baumgartner and R. Scheiber},
    title = {Multi-mode Real-Time {SAR} On-Board Processing},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    month = jun,
    pages = {1--6},
    owner = {ofrey},
    
    }
    


  19. R. Que, Octavio Ponce, Rolf Scheiber, and Andreas Reigber. Real-time processing of SAR images for linear and non-linear tracks. In Proc. 17th Int. Radar Symp. (IRS), pages 1-4, May 2016. Keyword(s): airborne radar, backpropagation, radar imaging, synthetic aperture radar, DLR's F-SAR sensor, GPU, SAR images, airborne SAR, direct backprojection, distributed real-time processing, fast factorized back-projection algorithms, linear tracks, multiprocessors multicore CPU, nonlinear tracks, real-time computation, Containers, Graphics processing units, Instruction sets, Interpolation, Radar tracking, Real-time systems, Synthetic aperture radar.
    @InProceedings{quePonceScheiberReigber2016a,
    author = {R. Que and Octavio Ponce and Rolf Scheiber and Andreas Reigber},
    title = {Real-time processing of {SAR} images for linear and non-linear tracks},
    booktitle = {Proc. 17th Int. Radar Symp. (IRS)},
    year = {2016},
    month = may,
    pages = {1--4},
    doi = {10.1109/IRS.2016.7497304},
    keywords = {airborne radar, backpropagation, radar imaging, synthetic aperture radar, DLR's F-SAR sensor, GPU, SAR images, airborne SAR, direct backprojection, distributed real-time processing, fast factorized back-projection algorithms, linear tracks, multiprocessors multicore CPU, nonlinear tracks, real-time computation, Containers, Graphics processing units, Instruction sets, Interpolation, Radar tracking, Real-time systems, Synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  20. M. Adnan Siddique, Urs Wegmuller, Irena Hajnsek, and Othmar Frey. SAR tomography as an add-on to PSI for improved deformation sampling in urban areas: a quality assessment. In Proc. of EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar, pages 669-612, June 2016. Keyword(s): SAR Processing, SAR tomography, Synthetic aperture radar (SAR), SAR Interferometry, InSAR, interferometric stacking, persistent scatterer interferometry, PSI, spaceborne SAR radar interferometry, spaceborne radar, X-Band, TerraSAR-X, synthetic aperture radar, tomography, 3-D point cloud retrieval, Barcelona, SAR tomography based 3-D point cloud extraction, high-resolution spaceborne TerraSAR-X data, interferometric stack, high-rise building vertical tomographic slice, layover scenario case, persistent scatterer interferometry, PSI, point-like scatterer, processing approach, Urban Remote Sensing, Spaceborne radar, Synthetic aperture radar, Three-dimensional displays, Tomography, 3-D point cloud, SAR interferometry.
    Abstract: Persistent scatterer interferometry (PSI) typically rejects layovers. Therefore, layover-affected urban areas may suffer from inadequate deformation sampling. SAR tomography, when used as an add-on to PSI, reveals additional deformation samples by resolving layovers. In this paper we quantify the relative gain in deformation sampling, while taking into account the quality of the additional (double) scatterers in terms of root-mean-square (RMS) phase deviation. We experiment on an interferometric stack of 50 TerraSAR-X stripmap images acquired over the city of Barcelona. The results show a tradeoff between the gain and the quality of the detected scatterers. For the observed urban area, we obtain a gain of 9.8% while the RMS phase deviation for 99% of the detected double scatterers is less than 1.1 radians.

    @InProceedings{siddiqueWegmullerHajnsekFreyEUSAR2016PSITomo,
    author = {Siddique, M. Adnan and Wegmuller, Urs and Hajnsek, Irena and Frey, Othmar},
    title = {SAR tomography as an add-on to PSI for improved deformation sampling in urban areas: a quality assessment},
    booktitle = {Proc. of EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar},
    year = {2016},
    pages = {669-612},
    month = jun,
    abstract = {Persistent scatterer interferometry (PSI) typically rejects layovers. Therefore, layover-affected urban areas may suffer from inadequate deformation sampling. SAR tomography, when used as an add-on to PSI, reveals additional deformation samples by resolving layovers. In this paper we quantify the relative gain in deformation sampling, while taking into account the quality of the additional (double) scatterers in terms of root-mean-square (RMS) phase deviation. We experiment on an interferometric stack of 50 TerraSAR-X stripmap images acquired over the city of Barcelona. The results show a tradeoff between the gain and the quality of the detected scatterers. For the observed urban area, we obtain a gain of 9.8% while the RMS phase deviation for 99% of the detected double scatterers is less than 1.1 radians.},
    file = {:siddiqueWegmullerHajnsekFreyEUSAR2016PSITomo.pdf:PDF},
    keywords = {SAR Processing, SAR tomography; Synthetic aperture radar (SAR); SAR Interferometry, InSAR, interferometric stacking;persistent scatterer interferometry; PSI, spaceborne SAR radar interferometry;spaceborne radar; X-Band, TerraSAR-X, synthetic aperture radar;tomography;3-D point cloud retrieval; Barcelona; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne TerraSAR-X data, interferometric stack;high-rise building vertical tomographic slice; layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Urban Remote Sensing; Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWegmullerHajnsekFreyEUSAR2016PSITomo.pdf},
    url = {http://ieeexplore.ieee.org/document/7559388},
    
    }
    


  21. Muhammad Adnan Siddique, Urs Wegmuller, Irena Hajnsek, and Othmar Frey. SAR tomography as an add-on to PSI: gain in deformation sampling vis-a-vis quality of the detected scatterers. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 1452-1455, July 2016. Keyword(s): SAR Processing, SAR tomography, Synthetic aperture radar (SAR), SAR Interferometry, InSAR, interferometric stacking, persistent scatterer interferometry, PSI, spaceborne SAR radar interferometry, spaceborne radar, X-Band, TerraSAR-X, synthetic aperture radar, tomography, 3-D point cloud retrieval, Barcelona, SAR tomography based 3-D point cloud extraction, high-resolution spaceborne TerraSAR-X data, interferometric stack, high-rise building vertical tomographic slice, layover scenario case, persistent scatterer interferometry, PSI, point-like scatterer, processing approach, Urban Remote Sensing, Spaceborne radar, Synthetic aperture radar, Three-dimensional displays, Tomography, 3-D point cloud, SAR interferometry.
    Abstract: SAR tomography can be used as an add-on to persistent scatterer interferometry (PSI) to increase deformation sampling in urban areas by resolving the frequently occurring layovers that are by definition rejected in the PSI processing. This paper, while focusing on the case of a typical highrise building in layover, quantitatively assesses the potential gain in deformation sampling achieved by the added use of an advanced SAR tomographic technique relative to a PSI approach. At the same time, the quantity of the detected scatterers is weighed against their quality, as assessed on the basis of root-mean-square (RMS) phase deviation between the measurements and the model fit. The quality of the scatterers is also compared with the quality of the persistent scatterers as identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap mode images. The results show that although there is a trade-off between the quantity and the quality of the scatterers, SAR tomography effectively resolves the layovers for the test site and provides an improvement in deformation sampling.

    @InProceedings{siddiqueWegmullerHajnsekFreyIGARSS2016PSITomo,
    author = {Muhammad Adnan Siddique and Urs Wegmuller and Irena Hajnsek and Othmar Frey},
    title = {SAR tomography as an add-on to PSI: gain in deformation sampling vis-a-vis quality of the detected scatterers},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2016},
    pages = {1452-1455},
    month = jul,
    abstract = {SAR tomography can be used as an add-on to persistent scatterer interferometry (PSI) to increase deformation sampling in urban areas by resolving the frequently occurring layovers that are by definition rejected in the PSI processing. This paper, while focusing on the case of a typical highrise building in layover, quantitatively assesses the potential gain in deformation sampling achieved by the added use of an advanced SAR tomographic technique relative to a PSI approach. At the same time, the quantity of the detected scatterers is weighed against their quality, as assessed on the basis of root-mean-square (RMS) phase deviation between the measurements and the model fit. The quality of the scatterers is also compared with the quality of the persistent scatterers as identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap mode images. The results show that although there is a trade-off between the quantity and the quality of the scatterers, SAR tomography effectively resolves the layovers for the test site and provides an improvement in deformation sampling.},
    doi = {10.1109/IGARSS.2016.7729371},
    file = {:siddiqueWegmullerHajnsekFreyIGARSS2016PSITomo.pdf:PDF},
    keywords = {SAR Processing, SAR tomography; Synthetic aperture radar (SAR); SAR Interferometry, InSAR, interferometric stacking;persistent scatterer interferometry; PSI, spaceborne SAR radar interferometry;spaceborne radar; X-Band, TerraSAR-X, synthetic aperture radar;tomography;3-D point cloud retrieval; Barcelona; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne TerraSAR-X data, interferometric stack;high-rise building vertical tomographic slice; layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Urban Remote Sensing; Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWegmullerHajnsekFreyIGARSS2016PSITomo.pdf},
    url = {http://ieeexplore.ieee.org/document/7729371},
    
    }
    


  22. Urs Wegmuller, Charles L. Werner, Andreas Wiesmann, Penelope Kourkouli, and Othmar Frey. Time-series analysis of Sentinel-1 interferometric wide swath data: techniques and challanges. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 1, pages 3898-3901, July 2016. Keyword(s): SAR Processing, SAR Interferometry, InSAR, differential SAR interferometry, D-InSAR, TOPS interferometry, TOPS mode, Sentinel-1, Spaceborne SAR, C-Band.
    @InProceedings{wegmullerWernerWiesmannStrozziKourkouliFreyIGARSS2016Sentinel1TimeSeries,
    author = {Urs Wegmuller and Charles L. Werner and Andreas Wiesmann and Penelope Kourkouli and Othmar Frey},
    title = {Time-series analysis of Sentinel-1 interferometric wide swath data: techniques and challanges},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2016},
    volume = {1},
    pages = {3898-3901},
    month = jul,
    doi = {10.1109/IGARSS.2016.7730012},
    file = {:wegmullerWernerWiesmannStrozziKourkouliFreyIGARSS2016Sentinel1TimeSeries.pdf:PDF},
    keywords = {SAR Processing, SAR Interferometry, InSAR, differential SAR interferometry, D-InSAR, TOPS interferometry, TOPS mode, Sentinel-1, Spaceborne SAR, C-Band},
    owner = {ofrey},
    url = {http://ieeexplore.ieee.org/document/7730012},
    
    }
    


  23. T. M. d. Hoyo and O. Ponce. Understanding Spaceborne Missions for TomoSAR Imaging with Multi-Angular Acquisitions. In Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar, pages 1-4, June 2016.
    @InProceedings{Hoyo2016,
    author = {T. M. d. Hoyo and O. Ponce},
    title = {Understanding Spaceborne Missions for TomoSAR Imaging with Multi-Angular Acquisitions},
    booktitle = {Proc. EUSAR 2016: 11th European Conf. Synthetic Aperture Radar},
    year = {2016},
    month = jun,
    pages = {1--4},
    owner = {ofrey},
    
    }
    


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Please note that access to full text PDF versions of papers is restricted to the Chair of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich.
Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.

This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.




Last modified: Mon Feb 1 16:39:00 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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