BACK TO INDEX BACK TO OTHMAR FREY'S HOMEPAGE

Publications of year 2017

Thesis

  1. S. Samie Esfahany. Exploitation of distributed scatterers in synthetic aperture radar interferometry. PhD thesis, TUDelft, 2017.
    Abstract: uring the last decades, time-series interferometric synthetic aperture radar (InSAR) has emerged as a powerful technique to measure various surface deformation phenomena of the earth. Early generations of time-series InSAR methodologies, i.e. Persistent Scatterer Interferometry (PSI), focused on point targets, which are mainly man-made features with a high density in urban areas and associated infrastructure. Later, methodologies were introduced aiming to extract information from other targets known as distributed scatterers (DS), which are associated with ground resolution cells occurring mainly in rural areas. Unfortunately, the underlying properties and assumptions behind various DS-phase estimation methodologies are sometimes subjective and incomparable, which hampers the objective application of the different methods. Moreover, for some terrain types, such as agricultural terrain or pastures, the feasibility of DS-methodologies is not straightforward.In view of these challenges, the two main objectives of this study are (i) to formulate and implement the estimation methodology of DS-pixels in a standard geodetic framework and to compare it with other existing methods, and (ii) to assess the feasibility of exploiting distributed scatterers for deformation monitoring over agricultural and pasture areas.We review state-of-the-art time-series InSAR methodologies with special attention toprocessing aspects related to distributed scatterers. From an estimation theory perspective, the key processing step to extract information from DS-pixels is the equivalent single-master (ESM) phase estimation. To situate this estimation in a geodetic framework, a mathematical model is proposed in the form of a Gauss-Markov model. To evaluate the stochastic part of the model, a numerical Monte-Carlo methodology as well as an analytical approach are introduced. Regarding the functional part, the ESM-phase estimation is formulated in the form of a hybrid linear system of observation-equations with both real-value and integer unknowns. The solution of the proposed model is given by the integer least-squares (ILS) estimator. The properties of such an estimator for ESM-phase estimation are described and demonstrated using synthetic and real datasets. Furthermore, to provide a theoretical comparison between the proposed ILS estimator and other existing ESM-phase estimators, a unified mathematical model in the form of a system of observation equations is proposed. Evaluating all the existing DS-methods shows that, although they all provide specific solutions, their fundamental difference is in how they assign weights to the interferometric observations.The feasibility of exploiting PS, DS, and their combination over agricultural and rurallandscapes is assessed via a case study on a subsidence area near city of Veendam,the Netherlands, based on the coherence behavior of different types of land use. It isshown that, under the condition of using the entire time-series, agricultural and pasture areas show only limited improvement in point density compared to the results of PSonly processing. This is due to the seasonal behavior of the temporal coherence, which causes an almost complete drop in coherence during summer periods, mainly as a result of tillage, crop growth and harvesting.To model this periodicity, a new analytical model is introduced. In this model, the hypothetical movements of elementary scatterers within DS resolution cells are modeled as a stochastic process with non-stationary but periodic increments. The parameters of this model are estimated for pasture areas, and are subsequently used to assess the feasibility of exploiting DS-pixels in agricultural areas by different satellite missions. The results confirm that, assuming a three-year stack of data, the information content in DS-pixels from current C-band and X-band missions is not enough for the successful utilization of their entire time-series. However by using intermittent series, e.g., by processing individual coherent periods, the results indicate that DS-pixels can be exploited: based on the proposed decorrelation model, the short repeat times of Sentinel-1 (6 or 12 days) results in a sufficient number of coherent interferograms over each winter period, enabling DS exploitation even over agricultural and pasture areas.

    @PhdThesis{samieiEsfahanyPhDThesisDistributedScatterersInSAR,
    author = {Samie Esfahany, S.},
    school = {TUDelft},
    title = {Exploitation of distributed scatterers in synthetic aperture radar interferometry},
    year = {2017},
    abstract = {uring the last decades, time-series interferometric synthetic aperture radar (InSAR) has emerged as a powerful technique to measure various surface deformation phenomena of the earth. Early generations of time-series InSAR methodologies, i.e. Persistent Scatterer Interferometry (PSI), focused on point targets, which are mainly man-made features with a high density in urban areas and associated infrastructure. Later, methodologies were introduced aiming to extract information from other targets known as distributed scatterers (DS), which are associated with ground resolution cells occurring mainly in rural areas. Unfortunately, the underlying properties and assumptions behind various DS-phase estimation methodologies are sometimes subjective and incomparable, which hampers the objective application of the different methods. Moreover, for some terrain types, such as agricultural terrain or pastures, the feasibility of DS-methodologies is not straightforward.In view of these challenges, the two main objectives of this study are (i) to formulate and implement the estimation methodology of DS-pixels in a standard geodetic framework and to compare it with other existing methods, and (ii) to assess the feasibility of exploiting distributed scatterers for deformation monitoring over agricultural and pasture areas.We review state-of-the-art time-series InSAR methodologies with special attention toprocessing aspects related to distributed scatterers. From an estimation theory perspective, the key processing step to extract information from DS-pixels is the equivalent single-master (ESM) phase estimation. To situate this estimation in a geodetic framework, a mathematical model is proposed in the form of a Gauss-Markov model. To evaluate the stochastic part of the model, a numerical Monte-Carlo methodology as well as an analytical approach are introduced. Regarding the functional part, the ESM-phase estimation is formulated in the form of a hybrid linear system of observation-equations with both real-value and integer unknowns. The solution of the proposed model is given by the integer least-squares (ILS) estimator. The properties of such an estimator for ESM-phase estimation are described and demonstrated using synthetic and real datasets. Furthermore, to provide a theoretical comparison between the proposed ILS estimator and other existing ESM-phase estimators, a unified mathematical model in the form of a system of observation equations is proposed. Evaluating all the existing DS-methods shows that, although they all provide specific solutions, their fundamental difference is in how they assign weights to the interferometric observations.The feasibility of exploiting PS, DS, and their combination over agricultural and rurallandscapes is assessed via a case study on a subsidence area near city of Veendam,the Netherlands, based on the coherence behavior of different types of land use. It isshown that, under the condition of using the entire time-series, agricultural and pasture areas show only limited improvement in point density compared to the results of PSonly processing. This is due to the seasonal behavior of the temporal coherence, which causes an almost complete drop in coherence during summer periods, mainly as a result of tillage, crop growth and harvesting.To model this periodicity, a new analytical model is introduced. In this model, the hypothetical movements of elementary scatterers within DS resolution cells are modeled as a stochastic process with non-stationary but periodic increments. The parameters of this model are estimated for pasture areas, and are subsequently used to assess the feasibility of exploiting DS-pixels in agricultural areas by different satellite missions. The results confirm that, assuming a three-year stack of data, the information content in DS-pixels from current C-band and X-band missions is not enough for the successful utilization of their entire time-series. However by using intermittent series, e.g., by processing individual coherent periods, the results indicate that DS-pixels can be exploited: based on the proposed decorrelation model, the short repeat times of Sentinel-1 (6 or 12 days) results in a sufficient number of coherent interferograms over each winter period, enabling DS exploitation even over agricultural and pasture areas.},
    doi = {10.4233/uuid:22d46f1e-9061-46b0-9726-760c41404b6f},
    owner = {ofrey},
    
    }
    


Articles in journal or book chapters

  1. Othmar Frey. Synthetic Aperture Radar. In Douglas Richardson, editor, International Encyclopedia of Geography: People, the Earth, Environment, and Technology, pages 1-24. Wiley, 2017. Keyword(s): Synthetic Aperture Radar, SAR, Imaging, microwave imaging, radar systems, biosphere, carbon sequestration, co-seismic displacement, crustal deformation, data acquisition, digital earth, earth observation, earth system science, geocomputation, geodesy, geohazards, geomatics, geophysical signal processing, geospatial information, GIScience, ground deformation/subsidence monitoring, interferometry, land cover, land use change, mapping, microwave remote sensing, polarimetry, radar remote sensing, remote sensing, topography, volcano monitoring.
    Abstract: In this entry, the basic principles of synthetic aperture radar imaging are introduced from a general physics perspective instead of tackling the topic from the more widespread signal processing point of view. Thus, the material is thought to be accessible to any scientist or the general reader with some basic knowledge of physics and calculus. The focus is on explaining the imaging concept of synthetic aperture radar. Most of the applications based on remote sensing with synthetic aperture radar systems make use of advanced technologies that have been built on top of synthetic aperture radar (SAR) imagery. Such technologies include: SAR interferometry, differential SAR interferometry, persistent scatterer interferometry, and more recently, SAR polarimetric interferometry, and SAR tomography. A plethora of applications are supported - or, partly, were made available only - by these SAR-based techniques. Examples of such applications include: topographic mapping, change detection, land cover classification, ground deformation/subsidence monitoring, measurement of co-seismic displacements, crustal deformation and volcano monitoring, remote sensing of the cryosphere, remote sensing of the biosphere, quantification of carbon sequestration, and, in general, monitoring tasks requiring day/night, all-weather availability.

    @InCollection{freySARChapterEncyclopediaOfGeography2016,
    author = {Othmar Frey},
    title = {Synthetic Aperture Radar},
    booktitle = {International Encyclopedia of Geography: People, the Earth, Environment, and Technology},
    publisher = {Wiley},
    year = {2017},
    editor = {Douglas Richardson},
    pages = {1-24},
    abstract = {In this entry, the basic principles of synthetic aperture radar imaging are introduced from a general physics perspective instead of tackling the topic from the more widespread signal processing point of view. Thus, the material is thought to be accessible to any scientist or the general reader with some basic knowledge of physics and calculus. The focus is on explaining the imaging concept of synthetic aperture radar. Most of the applications based on remote sensing with synthetic aperture radar systems make use of advanced technologies that have been built on top of synthetic aperture radar (SAR) imagery. Such technologies include: SAR interferometry, differential SAR interferometry, persistent scatterer interferometry, and more recently, SAR polarimetric interferometry, and SAR tomography. A plethora of applications are supported - or, partly, were made available only - by these SAR-based techniques. Examples of such applications include: topographic mapping, change detection, land cover classification, ground deformation/subsidence monitoring, measurement of co-seismic displacements, crustal deformation and volcano monitoring, remote sensing of the cryosphere, remote sensing of the biosphere, quantification of carbon sequestration, and, in general, monitoring tasks requiring day/night, all-weather availability.},
    doi = {10.1002/9781118786352.wbieg0115},
    file = {:freySARChapterEncyclopediaOfGeography2016.pdf:PDF},
    keywords = {Synthetic Aperture Radar, SAR, Imaging, microwave imaging;radar systems,biosphere;carbon sequestration;co-seismic displacement;crustal deformation;data acquisition;digital earth;earth observation;earth system science;geocomputation;geodesy;geohazards;geomatics;geophysical signal processing;geospatial information;GIScience;ground deformation/subsidence monitoring;interferometry;land cover;land use change;mapping;microwave remote sensing;polarimetry;radar remote sensing;remote sensing;topography;volcano monitoring},
    organization = {AAG},
    url = {http://onlinelibrary.wiley.com/doi/10.1002/9781118786352.wbieg0115/pdf},
    
    }
    


  2. Homa Ansari, Francesco De Zan, and Richard Bamler. Sequential Estimator: Toward Efficient InSAR Time Series Analysis. IEEE Transactions on Geoscience and Remote Sensing, 55(10):5637-5652, October 2017. Keyword(s): SAR Processing, SAR Interferometry, InSAR, differential SAR interferometry, D-InSAR, covariance matrices, data compression, image coding, radar imaging, radar interferometry, synthetic aperture radar, time series, Big Data, InSAR time series analysis, compressed data batch artificial interferograms, data batch compression, data covariance matrix analysis, data reduction, high-precision near-real-time processing, interferometric phase estimation, recursive estimation, sequential estimator, virtual image estimator, wide-swath synthetic aperture radar mission, Coherence, Earth, Maximum likelihood estimation, Monitoring, Synthetic aperture radar, Time series analysis, Big Data, coherence estimation error, data compression, differential interferometric synthetic aperture radar (DInSAR), distributed scatterers, efficiency, error analysis, low-rank approximation, maximum-likelihood estimation (MLE).
    Abstract: Wide-swath synthetic aperture radar (SAR) missions with short revisit times, such as Sentinel-1 and the planned NISAR and Tandem-L, provide an unprecedented wealth of interferometric SAR (InSAR) time series. However, the processing of the emerging Big Data is challenging for state-of-the-art InSAR analysis techniques. This contribution introduces a novel approach, named Sequential Estimator, for efficient estimation of the interferometric phase from long InSAR time series. The algorithm uses recursive estimation and analysis of the data covariance matrix via division of the data into small batches, followed by the compression of the data batches. From each compressed data batch artificial interferograms are formed, resulting in a strong data reduction. Such interferograms are used to link the older data batches with the most recent acquisitions and thus to reconstruct the phase time series. This scheme avoids the necessity of reprocessing the entire data stack at the face of each new acquisition. The proposed estimator introduces negligible degradation compared to the Cramer-Rao lower bound under realistic coherence scenarios. The estimator may therefore be adapted for high-precision near-real-time processing of InSAR and accommodate the conversion of InSAR from an offline to a monitoring geodetic tool. The performance of the Sequential Estimator is compared to state-of-the-art techniques via simulations and application to Sentinel-1 data.

    @Article{ansariDeZanBamlerTGRS2017SequentialEstimatorNRTInSARProcessing,
    author = {Ansari, Homa and De Zan, Francesco and Bamler, Richard},
    title = {Sequential Estimator: Toward Efficient {InSAR} Time Series Analysis},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2017},
    volume = {55},
    number = {10},
    pages = {5637-5652},
    month = oct,
    issn = {0196-2892},
    abstract = {Wide-swath synthetic aperture radar (SAR) missions with short revisit times, such as Sentinel-1 and the planned NISAR and Tandem-L, provide an unprecedented wealth of interferometric SAR (InSAR) time series. However, the processing of the emerging Big Data is challenging for state-of-the-art InSAR analysis techniques. This contribution introduces a novel approach, named Sequential Estimator, for efficient estimation of the interferometric phase from long InSAR time series. The algorithm uses recursive estimation and analysis of the data covariance matrix via division of the data into small batches, followed by the compression of the data batches. From each compressed data batch artificial interferograms are formed, resulting in a strong data reduction. Such interferograms are used to link the older data batches with the most recent acquisitions and thus to reconstruct the phase time series. This scheme avoids the necessity of reprocessing the entire data stack at the face of each new acquisition. The proposed estimator introduces negligible degradation compared to the Cramer-Rao lower bound under realistic coherence scenarios. The estimator may therefore be adapted for high-precision near-real-time processing of InSAR and accommodate the conversion of InSAR from an offline to a monitoring geodetic tool. The performance of the Sequential Estimator is compared to state-of-the-art techniques via simulations and application to Sentinel-1 data.},
    doi = {10.1109/TGRS.2017.2711037},
    file = {:ansariDeZanBamlerTGRS2017SequentialEstimatorNRTInSARProcessing.pdf:PDF},
    keywords = {SAR Processing, SAR Interferometry, InSAR, differential SAR interferometry, D-InSAR, covariance matrices;data compression;image coding;radar imaging;radar interferometry;synthetic aperture radar;time series;Big Data;InSAR time series analysis;compressed data batch artificial interferograms;data batch compression;data covariance matrix analysis;data reduction;high-precision near-real-time processing;interferometric phase estimation;recursive estimation;sequential estimator;virtual image estimator;wide-swath synthetic aperture radar mission;Coherence;Earth;Maximum likelihood estimation;Monitoring;Synthetic aperture radar;Time series analysis;Big Data;coherence estimation error;data compression;differential interferometric synthetic aperture radar (DInSAR);distributed scatterers;efficiency;error analysis;low-rank approximation;maximum-likelihood estimation (MLE)},
    owner = {ofrey},
    pdf = {../../../docs/ansariDeZanBamlerTGRS2017SequentialEstimatorNRTInSARProcessing.pdf},
    
    }
    


  3. A. E. A. Blomberg, T. O. Saebo, Roy E. Hansen, R. B. Pedersen, and A. Austeng. Automatic Detection of Marine Gas Seeps Using an Interferometric Sidescan Sonar. IEEE Journal of Oceanic Engineering, 42(3):590-602, July 2017. Keyword(s): Synthetic Aperture Sonar, SAS, carbon capture and storage, interferometry, oceanographic techniques, seafloor phenomena, sediments, sonar, underwater sound, volcanology, North Sea, acoustic backscatter properties, acoustic seep detection, automatic seep detection method, autonomous underwater vehicle, biogenic methane, gravel, interferometric sidescan sonar, man-made constructions, marine gas seep automatic detection, marine gas seep detection method, marine gas seep monitoring method, multibeam surveying, ocean greenhouse gases, pipelines, sandy seafloor, seafloor seeps, seafloor types, sediments, seep acoustical property, seep spatial property, sidescan surveying, signal processing techniques, silt, subseafloor CO2 storage sites, volcano CO2 release, water gas-filled bubbles, well heads, Acoustics, Backscatter, Damping, Monitoring, Resonant frequency, Sonar detection, Automatic leakage detection, carbon capture and storage (CCS) monitoring, coherence, gas seep detection, interferometric sonar, sidescan sonar.
    Abstract: There is a significant need for reliable, cost-effective, and preferably automatic methods for detecting and monitoring marine gas seeps. Seeps at the seafloor may originate from natural sources including sediments releasing biogenic methane and volcanoes releasing CO2, or from man-made constructions such as pipelines or well heads, and potentially also from subseafloor CO2 storage sites. Improved seep detection makes it possible to estimate the amount of greenhouse gases entering the oceans, and to promptly detect and address potential leaks to reduce environmental and economical consequences. Sonar is an excellent tool for seep detection due to the strong acoustic backscatter properties of gas-filled bubbles in water. Existing methods for acoustic seep detection include multibeam and sidescan surveying, as well as active and passive sensors mounted on a stationary platform. In this work, we develop a new method for automatic seep detection using an interferometric sidescan sonar. We apply signal processing techniques combined with knowledge about acoustical and spatial properties of seeps for improved detectability. The proposed method fills an important gap in existing technology-the ability to automatically detect a seep during a single pass with an autonomous underwater vehicle (AUV) equipped with an interferometric sidescan sonar. Results from simulations as well as field data from two leaking abandoned wells in the North Sea indicate that small seeps are consistently detected on a sandy seafloor even when the observation time is limited (a single pass with the AUV). We explore the detection capability for different seafloor types ranging from silt to gravel.

    @Article{blombergSaeboHansenPedersenAustengJOE2017DetectionUsingInterferometricSonar,
    author = {A. E. A. Blomberg and T. O. Saebo and Roy E. Hansen and R. B. Pedersen and A. Austeng},
    title = {Automatic Detection of Marine Gas Seeps Using an Interferometric Sidescan Sonar},
    journal = {IEEE Journal of Oceanic Engineering},
    year = {2017},
    volume = {42},
    number = {3},
    pages = {590-602},
    month = {July},
    issn = {0364-9059},
    abstract = {There is a significant need for reliable, cost-effective, and preferably automatic methods for detecting and monitoring marine gas seeps. Seeps at the seafloor may originate from natural sources including sediments releasing biogenic methane and volcanoes releasing CO2, or from man-made constructions such as pipelines or well heads, and potentially also from subseafloor CO2 storage sites. Improved seep detection makes it possible to estimate the amount of greenhouse gases entering the oceans, and to promptly detect and address potential leaks to reduce environmental and economical consequences. Sonar is an excellent tool for seep detection due to the strong acoustic backscatter properties of gas-filled bubbles in water. Existing methods for acoustic seep detection include multibeam and sidescan surveying, as well as active and passive sensors mounted on a stationary platform. In this work, we develop a new method for automatic seep detection using an interferometric sidescan sonar. We apply signal processing techniques combined with knowledge about acoustical and spatial properties of seeps for improved detectability. The proposed method fills an important gap in existing technology-the ability to automatically detect a seep during a single pass with an autonomous underwater vehicle (AUV) equipped with an interferometric sidescan sonar. Results from simulations as well as field data from two leaking abandoned wells in the North Sea indicate that small seeps are consistently detected on a sandy seafloor even when the observation time is limited (a single pass with the AUV). We explore the detection capability for different seafloor types ranging from silt to gravel.},
    doi = {10.1109/JOE.2016.2592559},
    file = {:blombergSaeboHansenPedersenAustengJOE2017DetectionUsingInterferometricSonar.pdf:PDF},
    keywords = {Synthetic Aperture Sonar, SAS,carbon capture and storage;interferometry;oceanographic techniques;seafloor phenomena;sediments;sonar;underwater sound;volcanology;North Sea;acoustic backscatter properties;acoustic seep detection;automatic seep detection method;autonomous underwater vehicle;biogenic methane;gravel;interferometric sidescan sonar;man-made constructions;marine gas seep automatic detection;marine gas seep detection method;marine gas seep monitoring method;multibeam surveying;ocean greenhouse gases;pipelines;sandy seafloor;seafloor seeps;seafloor types;sediments;seep acoustical property;seep spatial property;sidescan surveying;signal processing techniques;silt;subseafloor CO2 storage sites;volcano CO2 release;water gas-filled bubbles;well heads;Acoustics;Backscatter;Damping;Monitoring;Resonant frequency;Sonar detection;Automatic leakage detection;carbon capture and storage (CCS) monitoring;coherence;gas seep detection;interferometric sonar;sidescan sonar},
    
    }
    


  4. Alessandra Budillon, Angel Caroline Johnsy, and Gilda Schirinzi. Extension of a Fast GLRT Algorithm to 5D SAR Tomography of Urban Areas. Remote Sensing, 9(8), 2017. Keyword(s): SAR Processing, SAR Tomography, radar detection, GLRT, Fast GLRT, deformation, PSI, persistent scatterer interferometry, displacement mapping, 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: This paper analyzes a method for Synthetic Aperture Radar (SAR) Tomographic (TomoSAR) imaging, allowing the detection of multiple scatterers that can exhibit time deformation and thermal dilation by using a CFAR (Constant False Alarm Rate) approach. In the last decade, several methods for TomoSAR have been proposed. The objective of this paper is to present the results obtained on high resolution tomographic SAR data of urban areas, by using a statistical test for detecting multiple scatterers that takes into account phase variations due to possible deformations and/or thermal dilation. The test can be evaluated in terms of probability of detection (PD) and probability of false alarm (PFA), and is based on an approximation of a Generalized Likelihood Ratio Test (GLRT), denoted as Fast-Sup-GLRT. It was already applied and validated by the authors in the 3D case, while here it is extended and experimented in the 5D case. Numerical experiments on simulated and on StripMap TerraSAR-X (TSX) data have been carried out. The presented results show that the adopted method allows the detection of a large number of scatterers and the estimation of their position with a good accuracy, and that the consideration of the thermal dilation and surface deformation helps in recovering more single and double scatterers, with respect to the case in which these contributions are not taken into account. Moreover, the capability of method to provide reliable estimates of the deformations in urban structure suggests its use in structure stress monitoring.

    @Article{budillonJohnsySchirinziRemoteSensing2017FastGLRT5DTomo,
    author = {Budillon, Alessandra and Johnsy, Angel Caroline and Schirinzi, Gilda},
    title = {Extension of a Fast {GLRT} Algorithm to {5D} SAR Tomography of Urban Areas},
    journal = {Remote Sensing},
    year = {2017},
    volume = {9},
    number = {8},
    issn = {2072-4292},
    abstract = {This paper analyzes a method for Synthetic Aperture Radar (SAR) Tomographic (TomoSAR) imaging, allowing the detection of multiple scatterers that can exhibit time deformation and thermal dilation by using a CFAR (Constant False Alarm Rate) approach. In the last decade, several methods for TomoSAR have been proposed. The objective of this paper is to present the results obtained on high resolution tomographic SAR data of urban areas, by using a statistical test for detecting multiple scatterers that takes into account phase variations due to possible deformations and/or thermal dilation. The test can be evaluated in terms of probability of detection (PD) and probability of false alarm (PFA), and is based on an approximation of a Generalized Likelihood Ratio Test (GLRT), denoted as Fast-Sup-GLRT. It was already applied and validated by the authors in the 3D case, while here it is extended and experimented in the 5D case. Numerical experiments on simulated and on StripMap TerraSAR-X (TSX) data have been carried out. The presented results show that the adopted method allows the detection of a large number of scatterers and the estimation of their position with a good accuracy, and that the consideration of the thermal dilation and surface deformation helps in recovering more single and double scatterers, with respect to the case in which these contributions are not taken into account. Moreover, the capability of method to provide reliable estimates of the deformations in urban structure suggests its use in structure stress monitoring.},
    doi = {10.3390/rs9080844},
    file = {:budillonJohnsySchirinziRemoteSensing2017FastGLRT5DTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, radar detection; GLRT, Fast GLRT, deformation, PSI, persistent scatterer interferometry, displacement mapping, 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/budillonJohnsySchirinziRemoteSensing2017FastGLRT5DTomo.pdf},
    url = {http://www.mdpi.com/2072-4292/9/8/844},
    
    }
    


  5. J. I. Buskenes, Roy E. Hansen, and A. Austeng. Low-Complexity Adaptive Sonar Imaging. IEEE Journal of Oceanic Engineering, 42(1):87-96, January 2017. Keyword(s): Synthetic Aperture Sonar, SAS, Sonar, array signal processing, interference suppression, sonar imaging, DAS beamformer, Hamming window function, Kaiser window, Kongsberg Maritime HISAS1030 sonar, LCA beamformer, delay-and-sum beamformer, gain -3 dB, interference minimization, low-complexity adaptive sonar imaging, minimum variance distortionless response, parallel hardware, rectangular window function, robust MVDR implementation, spatial statistics, Array signal processing, Arrays, Covariance matrices, Image resolution, Imaging, Robustness, Sonar, Active, LCA, MVDR, active filters, adaptive beamforming, adaptive filters, beamforming, complexity, computational complexity, phased arrays, sonar, spatial filters.
    Abstract: We have studied the low-complexity adaptive (LCA) beamformer in active sonar imaging. LCA can be viewed as either a simplification of the minimum variance distortionless response (MVDR) beamformer, or as an adaptive extension to the delay-and-sum (DAS) beamformer. While both LCA and MVDR attempt to minimize the power of noise and interference in the image, MVDR achieves this by computing optimal array weights from the spatial statistics of the wavefield, while LCA selects the best performing weights out of a predefined set. To build confidence in the LCA method, we show that a robust MVDR implementation typically creates weight sets with shapes spanning between a rectangular and Hamming window function. We let LCA select from a set of Kaiser windows with responses in this span, and add some steered variations of each. We limit the steering to roughly half the -3-dB width of the window's amplitude response. Using experimental data from the Kongsberg Maritime HISAS1030 sonar we find that LCA and MVDR produce nearly identical images of large scenes, both being superior to DAS. On point targets LCA is able to double the resolution compared to DAS, or provide half that of MVDR. This performance is achieved with a total of six windows: the rectangular window and the Kaiser window with beta= 5, in an unsteered version, and versions that are left and right steered to the steering limit. Slightly smoother images are produced if the window count is increased to 15, but past this we observe minimal difference. Finally, we show that LCA works just as well if Kaiser windows are substituted with trigonometric ones. All our observations and experiences point to LCA being very easy to understand and manage. It simply works, and is surprisingly insensitive to the exact type of window function, steering amount, or number of windows. It can be efficiently implemented on parallel hardware, and handles any scene without the need for parameter adjustments.

    @Article{buskenesHansenAustengJOE2017AdaptiveSonarImaging,
    author = {J. I. Buskenes and Roy E. Hansen and A. Austeng},
    title = {Low-Complexity Adaptive Sonar Imaging},
    journal = {IEEE Journal of Oceanic Engineering},
    year = {2017},
    volume = {42},
    number = {1},
    pages = {87-96},
    month = jan,
    issn = {0364-9059},
    abstract = {We have studied the low-complexity adaptive (LCA) beamformer in active sonar imaging. LCA can be viewed as either a simplification of the minimum variance distortionless response (MVDR) beamformer, or as an adaptive extension to the delay-and-sum (DAS) beamformer. While both LCA and MVDR attempt to minimize the power of noise and interference in the image, MVDR achieves this by computing optimal array weights from the spatial statistics of the wavefield, while LCA selects the best performing weights out of a predefined set. To build confidence in the LCA method, we show that a robust MVDR implementation typically creates weight sets with shapes spanning between a rectangular and Hamming window function. We let LCA select from a set of Kaiser windows with responses in this span, and add some steered variations of each. We limit the steering to roughly half the -3-dB width of the window's amplitude response. Using experimental data from the Kongsberg Maritime HISAS1030 sonar we find that LCA and MVDR produce nearly identical images of large scenes, both being superior to DAS. On point targets LCA is able to double the resolution compared to DAS, or provide half that of MVDR. This performance is achieved with a total of six windows: the rectangular window and the Kaiser window with beta= 5, in an unsteered version, and versions that are left and right steered to the steering limit. Slightly smoother images are produced if the window count is increased to 15, but past this we observe minimal difference. Finally, we show that LCA works just as well if Kaiser windows are substituted with trigonometric ones. All our observations and experiences point to LCA being very easy to understand and manage. It simply works, and is surprisingly insensitive to the exact type of window function, steering amount, or number of windows. It can be efficiently implemented on parallel hardware, and handles any scene without the need for parameter adjustments.},
    doi = {10.1109/JOE.2016.2565038},
    file = {:buskenesHansenAustengJOE2017AdaptiveSonarImaging.pdf:PDF},
    keywords = {Synthetic Aperture Sonar, SAS,Sonar, array signal processing;interference suppression;sonar imaging;DAS beamformer;Hamming window function;Kaiser window;Kongsberg Maritime HISAS1030 sonar;LCA beamformer;delay-and-sum beamformer;gain -3 dB;interference minimization;low-complexity adaptive sonar imaging;minimum variance distortionless response;parallel hardware;rectangular window function;robust MVDR implementation;spatial statistics;Array signal processing;Arrays;Covariance matrices;Image resolution;Imaging;Robustness;Sonar;Active;LCA;MVDR;active filters;adaptive beamforming;adaptive filters;beamforming;complexity;computational complexity;phased arrays;sonar;spatial filters},
    
    }
    


  6. Jemil Butt, Andreas Wieser, and Stefan Conzett. Intrinsic random functions for mitigation of atmospheric effects in terrestrial radar interferometry. Journal of Applied Geodesy, 2017. Keyword(s): Atmospheric phase screen, radar interferometry, terrestrial radar interferometry ground-based radar, ground-based radar interferometry, intrinsic random functions, Kriging, IRF.
    @Article{buttWieserConzettJAG2017IntrinsicRandomFuncForAtmophere,
    author = {Jemil Butt and Andreas Wieser and Stefan Conzett},
    title = {Intrinsic random functions for mitigation of atmospheric effects in terrestrial radar interferometry},
    journal = {Journal of Applied Geodesy},
    year = {2017},
    keywords = {Atmospheric phase screen, radar interferometry, terrestrial radar interferometry ground-based radar, ground-based radar interferometry, intrinsic random functions, Kriging, IRF},
    owner = {ofrey},
    pdf = {../../../docs/buttWieserConzettJAG2017IntrinsicRandomFuncForAtmophere.pdf},
    
    }
    


  7. Ning Cao, Hyongki Lee, Evan Zaugg, R. Shrestha, W. Carter, C. Glennie, G. Wang, Z. Lu, and J. C. Fernandez-Diaz. Airborne DInSAR Results Using Time-Domain Backprojection Algorithm: A Case Study Over the Slumgullion Landslide in Colorado With Validation Using Spaceborne SAR, Airborne LiDAR, and Ground-Based Observations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(11):4987-5000, November 2017. Keyword(s): SAR Processing, Time-Domain Back-Projection, TDBP, Backprojection, Repeat-Pass Interferometry, SAR Interferometry, Displacement, Deformation Measurement, Aircraft, Interferometry, L-band, Spaceborne radar, Synthetic aperture radar, Terrain factors, Trajectory, Backprojection (BP), InSAR, SAR, differential synthetic aperture radar interferometry (DInSAR), landslide, motion compensation (MoCo), residual motion error (RME), Airborne SAR.
    Abstract: The major impediment to accurate airborne repeat-pass differential synthetic aperture radar (SAR) interferometry (DInSAR) is compensating for aircraft motion caused by air turbulence. Various motion compensation (MoCo) procedures have been used in the airborne DInSAR processing to acquire reliable deformation mapping. In this paper, we present the use of time-domain backprojection (BP) algorithm for SAR focusing in an airborne DInSAR survey: No MoCo procedure is needed because the BP algorithm is inherently able to compensate for platform motion. In this study, we present the results of a pilot study aimed at demonstrating the feasibility of deformation mapping with an airborne SAR system based on the monitoring of the Slumgullion landslide in Colorado, USA between July 3 and 10 of 2015. The employed airborne SAR system is an Artemis SlimSAR that is a compact, modular, and multi-frequency radar system. Airborne light detection and ranging and global navigation satellite system (GNSS) observations, as well as spaceborne DInSAR results using COSMO-SkyMed (CSK) images, were used to verify the performance of the airborne SAR system. The surface velocities of the landslide derived from the airborne DInSAR observations showed good agreement with the GNSS and spaceborne DInSAR estimates. A three-dimensional deformation map of the Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topographic variation. This study shows that an inexpensive airborne L-band DInSAR system has the potential to measure centimeter level deformation with flexible temporal and spatial baselines.

    @Article{caoLeeZauggEtAlJSTARS2017AirborneSARBackprojectionDInSAR,
    author = {Ning Cao and Hyongki Lee and Evan Zaugg and R. Shrestha and W. Carter and C. Glennie and G. Wang and Z. Lu and J. C. Fernandez-Diaz},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    title = {Airborne DInSAR Results Using Time-Domain Backprojection Algorithm: A Case Study Over the {Slumgullion} Landslide in {Colorado} With Validation Using Spaceborne {SAR}, Airborne {LiDAR}, and Ground-Based Observations},
    year = {2017},
    issn = {1939-1404},
    month = {Nov},
    number = {11},
    pages = {4987-5000},
    volume = {10},
    abstract = {The major impediment to accurate airborne repeat-pass differential synthetic aperture radar (SAR) interferometry (DInSAR) is compensating for aircraft motion caused by air turbulence. Various motion compensation (MoCo) procedures have been used in the airborne DInSAR processing to acquire reliable deformation mapping. In this paper, we present the use of time-domain backprojection (BP) algorithm for SAR focusing in an airborne DInSAR survey: No MoCo procedure is needed because the BP algorithm is inherently able to compensate for platform motion. In this study, we present the results of a pilot study aimed at demonstrating the feasibility of deformation mapping with an airborne SAR system based on the monitoring of the Slumgullion landslide in Colorado, USA between July 3 and 10 of 2015. The employed airborne SAR system is an Artemis SlimSAR that is a compact, modular, and multi-frequency radar system. Airborne light detection and ranging and global navigation satellite system (GNSS) observations, as well as spaceborne DInSAR results using COSMO-SkyMed (CSK) images, were used to verify the performance of the airborne SAR system. The surface velocities of the landslide derived from the airborne DInSAR observations showed good agreement with the GNSS and spaceborne DInSAR estimates. A three-dimensional deformation map of the Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topographic variation. This study shows that an inexpensive airborne L-band DInSAR system has the potential to measure centimeter level deformation with flexible temporal and spatial baselines.},
    doi = {10.1109/JSTARS.2017.2737362},
    file = {:caoLeeZauggEtAlJSTARS2017AirborneSARBackprojectionDInSAR.pdf:PDF},
    keywords = {SAR Processing, Time-Domain Back-Projection, TDBP, Backprojection, Repeat-Pass Interferometry, SAR Interferometry, Displacement, Deformation Measurement, Aircraft, Interferometry, L-band, Spaceborne radar, Synthetic aperture radar, Terrain factors, Trajectory, Backprojection (BP), InSAR, SAR, differential synthetic aperture radar interferometry (DInSAR), landslide, motion compensation (MoCo), residual motion error (RME), Airborne SAR},
    owner = {ofrey},
    pdf = {../../../docs/caoLeeZauggEtAlJSTARS2017AirborneSARBackprojectionDInSAR.pdf},
    
    }
    


  8. Victor Cazcarra-Bes, Marivi Tello-Alonso, Rico Fischer, Michael Heym, and Konstantinos Papathanassiou. Monitoring of Forest Structure Dynamics by Means of L-Band SAR Tomography. Remote Sensing, 9(12), 2017. Keyword(s): SAR Processing, SAR Tomography, Forestry, Synthetic aperture radar, Image reconstruction, Decorrelation, Estimation, forest applications, forest structure, Fourier beamforming (FB), L-band, synthetic aperture radar (SAR), tomography, L-Band, Airborne SAR.
    Abstract: Synthetic Aperture Radar Tomography (TomoSAR) allows the reconstruction of the 3D reflectivity of natural volume scatterers such as forests, thus providing an opportunity to infer structure information in 3D. In this paper, the potential of TomoSAR data at L-band to monitor temporal variations of forest structure is addressed using simulated and experimental datasets. First, 3D reflectivity profiles were extracted by means of TomoSAR reconstruction based on a Compressive Sensing (CS) approach. Next, two complementary indices for the description of horizontal and vertical forest structure were defined and estimated by means of the distribution of local maxima of the reconstructed reflectivity profiles. To assess the sensitivity and consistency of the proposed methodology, variations of these indices for different types of forest changes in simulated as well as in real scenarios were analyzed and assessed against different sources of reference data: airborne Lidar measurements, high resolution optical images, and forest inventory data. The forest structure maps obtained indicated the potential to distinguish between different forest stages and the identification of different types of forest structure changes induced by logging, natural disturbance, or forest management.

    @Article{cazcarraBesTelloAlonsoFischerHeymPapathanassiouRemoteSensing2017ForstStructureDynamicsLBandSARTomography,
    author = {Cazcarra-Bes, Victor and Tello-Alonso, Marivi and Fischer, Rico and Heym, Michael and Papathanassiou, Konstantinos},
    title = {Monitoring of Forest Structure Dynamics by Means of L-Band SAR Tomography},
    journal = {Remote Sensing},
    year = {2017},
    volume = {9},
    number = {12},
    issn = {2072-4292},
    abstract = {Synthetic Aperture Radar Tomography (TomoSAR) allows the reconstruction of the 3D reflectivity of natural volume scatterers such as forests, thus providing an opportunity to infer structure information in 3D. In this paper, the potential of TomoSAR data at L-band to monitor temporal variations of forest structure is addressed using simulated and experimental datasets. First, 3D reflectivity profiles were extracted by means of TomoSAR reconstruction based on a Compressive Sensing (CS) approach. Next, two complementary indices for the description of horizontal and vertical forest structure were defined and estimated by means of the distribution of local maxima of the reconstructed reflectivity profiles. To assess the sensitivity and consistency of the proposed methodology, variations of these indices for different types of forest changes in simulated as well as in real scenarios were analyzed and assessed against different sources of reference data: airborne Lidar measurements, high resolution optical images, and forest inventory data. The forest structure maps obtained indicated the potential to distinguish between different forest stages and the identification of different types of forest structure changes induced by logging, natural disturbance, or forest management.},
    article-number = {1229},
    doi = {10.3390/rs9121229},
    file = {:cazcarraBesTelloAlonsoFischerHeymPapathanassiouRemoteSensing2017ForstStructureDynamicsLBandSARTomography.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Forestry;Synthetic aperture radar;Image reconstruction;Decorrelation;Estimation;forest applications;forest structure;Fourier beamforming (FB);L-band;synthetic aperture radar (SAR);tomography, L-Band, Airborne SAR},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/9/12/1229},
    
    }
    


  9. Claudio De Luca, Ivana Zinno, Michele Manunta, Riccardo Lanari, and Francesco Casu. Large areas surface deformation analysis through a cloud computing P-SBAS approach for massive processing of DInSAR time series. Remote Sensing of Environment, 2017. Keyword(s): DInSAR, P-SBAS, Cloud computing, Mosaicking, ENVISAT, Sentinel-1.
    @Article{deLucaZinnoManuntaLanariCasuRSE2017CloudComputingPSBASDeformation,
    author = {De Luca, Claudio and Zinno, Ivana and Manunta, Michele and Lanari, Riccardo and Casu, Francesco},
    title = {Large areas surface deformation analysis through a cloud computing {P-SBAS} approach for massive processing of {DInSAR} time series},
    journal = {Remote Sensing of Environment},
    year = {2017},
    issn = {0034-4257},
    doi = {http://dx.doi.org/10.1016/j.rse.2017.05.022},
    url = {http://www.sciencedirect.com/science/article/pii/S0034425717302213},
    keywords = {DInSAR,P-SBAS,Cloud computing,Mosaicking,ENVISAT,Sentinel-1},
    owner = {ofrey},
    pdf = {../../../docs/deLucaZinnoManuntaLanariCasuRSE2017CloudComputingPSBASDeformation.pdf},
    
    }
    


  10. Masato Furuya, Takato Suzuki, Jun Maeda, and Kosuke Heki. Midlatitude sporadic-E episodes viewed by L-band split-spectrum InSAR. Earth, Planets and Space, 69(1):175, December 2017. Keyword(s): SAR Processing, SAR Interferometry, Interferometry, Split-Spectrum, Split-band, Split-Spectrum Interferometry, Split-band Interferometry, Total Electron Content Estimation, TEC Estimation, Ionospheric TEC, Faraday Rotation, Path Delay, Spaceborne SAR, L-Band, ALOS, Phased Array L-band SAR, PALSAR, Calibration, Ionosphere, Ionospheric Path Delay.
    Abstract: Sporadic-E (Es) is a layer of ionization that irregularly appears within the E region of the ionosphere and is known to generate an unusual propagation of very high frequency waves over long distances. The detailed spatial structure of Es remains unclear due to the limited spatial resolution in the conventional ionosonde observations. We detect midlatitude Es by interferometric synthetic aperture radar (InSAR), which can clarify the spatial structure of Es with unprecedented resolution. Moreover, we use the range split-spectrum method (SSM) to separate dispersive and nondispersive components in the InSAR image. While InSAR SSM largely succeeds in decomposing into dispersive and nondispersive signals, our results indicate that small-scale dispersive signals due to the total electron content anomalies are accompanied by nondispersive signals with similar spatial scale at the same locations. We also examine the effects of higher-order terms in the refractive index for dispersive media. Both of these detected Es episodes indicate that smaller-scale dispersive effects originate from higher-order effects. We interpret that the smaller-scale nondispersive signals could indicate the emergence of nitric oxide (NO) generated by the reactions of metals, Mg and Fe, with nitric oxide ion (NO+) during the Es.

    @Article{furuyaSuzukiMaedaHeki2017IonoLBandSplitSpectrumInSAR,
    author = {Furuya, Masato and Suzuki, Takato and Maeda, Jun and Heki, Kosuke},
    title = {Midlatitude sporadic-E episodes viewed by L-band split-spectrum InSAR},
    journal = {Earth, Planets and Space},
    year = {2017},
    volume = {69},
    number = {1},
    pages = {175},
    month = {Dec},
    issn = {1880-5981},
    abstract = {Sporadic-E (Es) is a layer of ionization that irregularly appears within the E region of the ionosphere and is known to generate an unusual propagation of very high frequency waves over long distances. The detailed spatial structure of Es remains unclear due to the limited spatial resolution in the conventional ionosonde observations. We detect midlatitude Es by interferometric synthetic aperture radar (InSAR), which can clarify the spatial structure of Es with unprecedented resolution. Moreover, we use the range split-spectrum method (SSM) to separate dispersive and nondispersive components in the InSAR image. While InSAR SSM largely succeeds in decomposing into dispersive and nondispersive signals, our results indicate that small-scale dispersive signals due to the total electron content anomalies are accompanied by nondispersive signals with similar spatial scale at the same locations. We also examine the effects of higher-order terms in the refractive index for dispersive media. Both of these detected Es episodes indicate that smaller-scale dispersive effects originate from higher-order effects. We interpret that the smaller-scale nondispersive signals could indicate the emergence of nitric oxide (NO) generated by the reactions of metals, Mg and Fe, with nitric oxide ion (NO+) during the Es.},
    day = {29},
    doi = {10.1186/s40623-017-0764-6},
    file = {:furuyaSuzukiMaedaHeki2017IonoLBandSplitSpectrumInSAR.pdf:PDF},
    keywords = {SAR Processing, SAR Interferometry, Interferometry, Split-Spectrum, Split-band, Split-Spectrum Interferometry, Split-band Interferometry,Total Electron Content Estimation, TEC Estimation, Ionospheric TEC, Faraday Rotation, Path Delay, Spaceborne SAR, L-Band, ALOS, Phased Array L-band SAR,PALSAR, Calibration, Ionosphere, Ionospheric Path Delay},
    owner = {ofrey},
    url = {https://doi.org/10.1186/s40623-017-0764-6},
    
    }
    


  11. Giorgio Gomba, Fernando Rodriguez Gonzalez, and Francesco De Zan. Ionospheric Phase Screen Compensation for the Sentinel-1 TOPS and ALOS-2 ScanSAR Modes. IEEE_J_GRS, 55(1):223-235, January 2017. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, ionospheric disturbances, total electron content (atmosphere), 2015 Nepal earthquake, 2016 Taiwan earthquake, ALOS-2 ScanSAR modes, ALOS-2 interferograms, C-band interferograms, Sentinel-1 TOPS, dispersive ionospheric component, interferometric measurements, ionospheric phase screen compensation, local global positioning system measurements, split-spectrum method, synthetic aperture radar acquisitions, total electron content maps, Azimuth, Correlation, Electrostatic discharges, Ionosphere, Satellites, Synthetic aperture radar, Timing, InSAR, SAR ionospheric effects, ionosphere estimation, split-spectrum.
    Abstract: Variations of the ionosphere can significantly disrupt synthetic aperture radar (SAR) acquisitions and interferometric measurements of ground deformation. In this paper, we show how the ionosphere can also strongly modify C-band interferograms despite its smaller influence at higher frequencies. Thus, ionospheric phase screens should not be neglected: their compensation improves the estimation of ground deformation maps. The split-spectrum method is able to estimate the dispersive ionospheric component of the interferometric phase; we describe the implementation of this method for the burst modes TOPS and ScanSAR to estimate and remove ionospheric phase screens. We present Sentinel-1 interferograms of the 2016 Taiwan earthquake and ALOS-2 interferograms of the 2015 Nepal earthquake, which show strong ionospheric phase gradients, and their corrected versions. Finally, to validate the results and better understand the origin of these ionospheric variations, we compare the estimated differential ionosphere with global Total Electron Content maps and local Global Positioning System measurements.

    @Article{gombaRodriguezGonzalezDeZanTGRS2017IonoSplitSpectrumInSAR,
    author = {Gomba, Giorgio and Rodriguez Gonzalez, Fernando and De Zan, Francesco},
    title = {Ionospheric Phase Screen Compensation for the Sentinel-1~{TOPS} and {ALOS}-2~{ScanSAR} Modes},
    journal = IEEE_J_GRS,
    year = {2017},
    volume = {55},
    number = {1},
    pages = {223--235},
    month = jan,
    issn = {0196-2892},
    abstract = {Variations of the ionosphere can significantly disrupt synthetic aperture radar (SAR) acquisitions and interferometric measurements of ground deformation. In this paper, we show how the ionosphere can also strongly modify C-band interferograms despite its smaller influence at higher frequencies. Thus, ionospheric phase screens should not be neglected: their compensation improves the estimation of ground deformation maps. The split-spectrum method is able to estimate the dispersive ionospheric component of the interferometric phase; we describe the implementation of this method for the burst modes TOPS and ScanSAR to estimate and remove ionospheric phase screens. We present Sentinel-1 interferograms of the 2016 Taiwan earthquake and ALOS-2 interferograms of the 2015 Nepal earthquake, which show strong ionospheric phase gradients, and their corrected versions. Finally, to validate the results and better understand the origin of these ionospheric variations, we compare the estimated differential ionosphere with global Total Electron Content maps and local Global Positioning System measurements.},
    doi = {10.1109/TGRS.2016.2604461},
    file = {:gombaRodriguezGonzalezDeZanTGRS2017IonoSplitSpectrumInSAR.pdf:PDF},
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, ionospheric disturbances, total electron content (atmosphere), 2015 Nepal earthquake, 2016 Taiwan earthquake, ALOS-2 ScanSAR modes, ALOS-2 interferograms, C-band interferograms, Sentinel-1 TOPS, dispersive ionospheric component, interferometric measurements, ionospheric phase screen compensation, local global positioning system measurements, split-spectrum method, synthetic aperture radar acquisitions, total electron content maps, Azimuth, Correlation, Electrostatic discharges, Ionosphere, Satellites, Synthetic aperture radar, Timing, InSAR, SAR ionospheric effects, ionosphere estimation, split-spectrum},
    owner = {ofrey},
    
    }
    


  12. G. Gomba and F. De Zan. Bayesian Data Combination for the Estimation of Ionospheric Effects in SAR Interferograms. IEEE_J_GRS, 55(11):6582-6593, November 2017. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, Bayes methods, Faraday effect, fractals, inverse problems, ionospheric electromagnetic wave propagation, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, Bayesian data combination, Bayesian inverse problem, Faraday rotation method, SAR images, SAR interferograms, advanced land observing satellite phased array type L-band SAR L-band images, azimuth mutual shifts, data-based model parameter estimation, differential ionospheric phase screen, error source, estimation accuracy, information sources, interferometric pair images, ionosphere turbulence, ionospheric effects estimation, ionospheric propagation path delay, physically realistic fractal modeling, range variations, sensitive azimuth shifts, simple split-spectrum method, small-scale azimuth variations, synthetic aperture radar interferograms, Azimuth, Bayes methods, Estimation, Extraterrestrial measurements, Faraday effect, Ionosphere, Synthetic aperture radar, Ionosphere estimation, SAR ionospheric effects, interferometric synthetic aperture radar (SAR), methods\textquoteright combination.
    Abstract: The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method.

    @Article{gombaDeZanTGRS2017IonoSplitSpectrumAndAzimuthShiftsBaysianComb,
    author = {G. Gomba and F. De Zan},
    title = {Bayesian Data Combination for the Estimation of Ionospheric Effects in {SAR} Interferograms},
    journal = IEEE_J_GRS,
    year = {2017},
    volume = {55},
    number = {11},
    pages = {6582--6593},
    month = nov,
    issn = {0196-2892},
    abstract = {The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method.},
    doi = {10.1109/TGRS.2017.2730438},
    file = {:gombaDeZanTGRS2017IonoSplitSpectrumAndAzimuthShiftsBaysianComb.pdf:PDF},
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry,Bayes methods, Faraday effect, fractals, inverse problems, ionospheric electromagnetic wave propagation, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, Bayesian data combination, Bayesian inverse problem, Faraday rotation method, SAR images, SAR interferograms, advanced land observing satellite phased array type L-band SAR L-band images, azimuth mutual shifts, data-based model parameter estimation, differential ionospheric phase screen, error source, estimation accuracy, information sources, interferometric pair images, ionosphere turbulence, ionospheric effects estimation, ionospheric propagation path delay, physically realistic fractal modeling, range variations, sensitive azimuth shifts, simple split-spectrum method, small-scale azimuth variations, synthetic aperture radar interferograms, Azimuth, Bayes methods, Estimation, Extraterrestrial measurements, Faraday effect, Ionosphere, Synthetic aperture radar, Ionosphere estimation, SAR ionospheric effects, interferometric synthetic aperture radar (SAR), methods{	extquoteright} combination},
    owner = {ofrey},
    
    }
    


  13. Céline Lamarche, Maurizio Santoro, Sophie Bontemps, Raphaël D'Andrimont, Julien Radoux, Laura Giustarini, Carsten Brockmann, Jan Wevers, Pierre Defourny, and Olivier Arino. Compilation and Validation of SAR and Optical Data Products for a Complete and Global Map of Inland/Ocean Water Tailored to the Climate Modeling Community. Remote Sensing, 9(1), 2017. Keyword(s): Remote Sensing, Water.
    Abstract: Accurate maps of surface water extent are of paramount importance for water management, satellite data processing and climate modeling. Several maps of water bodies based on remote sensing data have been released during the last decade. Nonetheless, none has a truly (90 deg N / 90 deg S) global coverage while being thoroughly validated. This paper describes a global, spatially-complete (void-free) and accurate mask of inland/ocean water for the 2000-2012 period, built in the framework of the European Space Agency (ESA) Climate Change Initiative (CCI). This map results from the synergistic combination of multiple individual SAR and optical water body and auxiliary datasets. A key aspect of this work is the original and rigorous stratified random sampling designed for the quality assessment of binary classifications where one class is marginally distributed. Input and consolidated products were assessed qualitatively and quantitatively against a reference validation database of 2110 samples spread throughout the globe. Using all samples, overall accuracy was always very high among all products, between 98% and 100%. The CCI global map of open water bodies provided the best water class representation (F-score of 89%) compared to its constitutive inputs. When focusing on the challenging areas for water bodies' mapping, such as shorelines, lakes and river banks, all products yielded substantially lower accuracy figures with overall accuracies ranging between 74% and 89%. The inland water area of the CCI global map of open water bodies was estimated to be 3.17 million km^2 +/- 0.24 million km^2. The dataset is freely available through the ESA CCI Land Cover viewer.

    @Article{lamarcheEtALRemoteSensing2017GlobalWaterMapFromSARandOptical,
    author = {Lamarche, C\'eline and Santoro, Maurizio and Bontemps, Sophie and D'Andrimont, Rapha\"el and Radoux, Julien and Giustarini, Laura and Brockmann, Carsten and Wevers, Jan and Defourny, Pierre and Arino, Olivier},
    title = {Compilation and Validation of SAR and Optical Data Products for a Complete and Global Map of Inland/Ocean Water Tailored to the Climate Modeling Community},
    journal = {Remote Sensing},
    year = {2017},
    volume = {9},
    number = {1},
    issn = {2072-4292},
    abstract = {Accurate maps of surface water extent are of paramount importance for water management, satellite data processing and climate modeling. Several maps of water bodies based on remote sensing data have been released during the last decade. Nonetheless, none has a truly (90 deg N / 90 deg S) global coverage while being thoroughly validated. This paper describes a global, spatially-complete (void-free) and accurate mask of inland/ocean water for the 2000-2012 period, built in the framework of the European Space Agency (ESA) Climate Change Initiative (CCI). This map results from the synergistic combination of multiple individual SAR and optical water body and auxiliary datasets. A key aspect of this work is the original and rigorous stratified random sampling designed for the quality assessment of binary classifications where one class is marginally distributed. Input and consolidated products were assessed qualitatively and quantitatively against a reference validation database of 2110 samples spread throughout the globe. Using all samples, overall accuracy was always very high among all products, between 98% and 100%. The CCI global map of open water bodies provided the best water class representation (F-score of 89%) compared to its constitutive inputs. When focusing on the challenging areas for water bodies' mapping, such as shorelines, lakes and river banks, all products yielded substantially lower accuracy figures with overall accuracies ranging between 74% and 89%. The inland water area of the CCI global map of open water bodies was estimated to be 3.17 million km^2 +/- 0.24 million km^2. The dataset is freely available through the ESA CCI Land Cover viewer.},
    article-number = {36},
    doi = {10.3390/rs9010036},
    file = {:lamarcheEtALRemoteSensing2017GlobalWaterMapFromSARandOptical.pdf:PDF},
    keywords = {Remote Sensing, Water},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/9/1/36},
    
    }
    


  14. Yang Lei, Paul Siqueira, and Robert Treuhaft. A physical scattering model of repeat-pass InSAR correlation for vegetation. Waves in Random and Complex Media, 27(1):129-152, 2017. Keyword(s): SAR Processing, Scattering Model, Interferometry, Correlation, Vegetation.
    Abstract: A physical scattering model of repeat-pass InSAR correlation over forested areas is derived by accounting for the changes in the dielectric properties and positions of the scatterers in the scene between overpasses. This derivation is based on the discrete representation of a sparse random medium (such as forest canopy) along with the solution to the Foldy-Lax multiple scattering equations. In addition to taking into account the random motion of scatterers, which has been investigated in previous work, the derived repeat-pass InSAR correlation model in this paper includes the effects of moisture-induced dielectric fluctuations. This is accomplished by incorporating a separate correlation profile that takes into account these fluctuations into the framework. Once constructed, the mathematical formulation of this scattering model is cast into a modified version of the Random Volume over Ground model such that it can separately take into account dielectric fluctuations in the ground and volume components. This model is then validated using a modified version of ESA's PolSARproSim simulation to show that similar results can be obtained from both the simulation and the theoretical model.

    @Article{leiSiqueiraTreuhaft2017ScatteringModelRepeatPassInSARCorrelationVegetation,
    author = {Yang Lei and Paul Siqueira and Robert Treuhaft},
    title = {A physical scattering model of repeat-pass InSAR correlation for vegetation},
    journal = {Waves in Random and Complex Media},
    year = {2017},
    volume = {27},
    number = {1},
    pages = {129-152},
    doi = {10.1080/17455030.2016.1209594},
    url = {http://dx.doi.org/10.1080/17455030.2016.1209594},
    abstract = {A physical scattering model of repeat-pass InSAR correlation over forested areas is derived by accounting for the changes in the dielectric properties and positions of the scatterers in the scene between overpasses. This derivation is based on the discrete representation of a sparse random medium (such as forest canopy) along with the solution to the Foldy-Lax multiple scattering equations. In addition to taking into account the random motion of scatterers, which has been investigated in previous work, the derived repeat-pass InSAR correlation model in this paper includes the effects of moisture-induced dielectric fluctuations. This is accomplished by incorporating a separate correlation profile that takes into account these fluctuations into the framework. Once constructed, the mathematical formulation of this scattering model is cast into a modified version of the Random Volume over Ground model such that it can separately take into account dielectric fluctuations in the ground and volume components. This model is then validated using a modified version of ESA's PolSARproSim simulation to show that similar results can be obtained from both the simulation and the theoretical model.},
    keywords = {SAR Processing, Scattering Model, Interferometry, Correlation, Vegetation},
    owner = {ofrey},
    
    }
    


  15. D. Li, M. Rodriguez-Cassola, P. Prats-Iraola, M. Wu, and A. Moreira. Reverse Backprojection Algorithm for the Accurate Generation of SAR Raw Data of Natural Scenes. IEEE Geoscience and Remote Sensing Letters, 14(11):2072-2076, November 2017. Keyword(s): data acquisition, geophysical image processing, remote sensing by radar, synthetic aperture radar, tropospheric electromagnetic wave propagation, reverse backprojection algorithm, SAR raw data, natural scenes, SAR image formation sibling, multistatic SAR missions, synthetic aperture radar mission concepts, geosynchronous SAR missions, observation geometry, acquisition strategy, atmospheric propagation, Synthetic aperture radar, Low earth orbit satellites, Azimuth, Atmospheric modeling, Standards, Algorithm design and analysis, Data models, Azimuth variation, backprojection algorithm, geosynchronous (GEO) SAR, raw data simulation, synthetic aperture radar (SAR), terrain observation with progressive scan (TOPS), tropospheric propagation.
    Abstract: Future synthetic aperture radar (SAR) mission concepts often rely on locally nonlinear (e.g., high orbits and bistatic) surveys or acquisition schemes. The simulation of the raw data of natural scenes as acquired by future systems appears as one powerful tool in order to understand the particularities of these systems and assess the impact of system and propagation errors on their performance. We put forward, in this letter, a new formulation of the reverse backprojection algorithm for the accurate simulation of raw data of natural surfaces. In particular, the algorithm is perfectly suited to accommodate any kind (1-D/2-D) of temporal and spatial variation, e.g., in observation geometry, acquisition strategy, or atmospheric propagation. The algorithm is analyzed with respect to its SAR image formation sibling, and tested under different simulation scenarios. We expect the reverse backprojection algorithm to play a relevant role in the simulation of future geosynchronous and multistatic SAR missions.

    @Article{liRodriguezPratsWuMoreiraGRSL2017ReverseBackprojectionForRawDataGeneration,
    author = {D. {Li} and M. {Rodriguez-Cassola} and P. {Prats-Iraola} and M. {Wu} and A. {Moreira}},
    title = {Reverse Backprojection Algorithm for the Accurate Generation of SAR Raw Data of Natural Scenes},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2017},
    volume = {14},
    number = {11},
    pages = {2072-2076},
    month = {Nov},
    issn = {1558-0571},
    abstract = {Future synthetic aperture radar (SAR) mission concepts often rely on locally nonlinear (e.g., high orbits and bistatic) surveys or acquisition schemes. The simulation of the raw data of natural scenes as acquired by future systems appears as one powerful tool in order to understand the particularities of these systems and assess the impact of system and propagation errors on their performance. We put forward, in this letter, a new formulation of the reverse backprojection algorithm for the accurate simulation of raw data of natural surfaces. In particular, the algorithm is perfectly suited to accommodate any kind (1-D/2-D) of temporal and spatial variation, e.g., in observation geometry, acquisition strategy, or atmospheric propagation. The algorithm is analyzed with respect to its SAR image formation sibling, and tested under different simulation scenarios. We expect the reverse backprojection algorithm to play a relevant role in the simulation of future geosynchronous and multistatic SAR missions.},
    doi = {10.1109/LGRS.2017.2751460},
    keywords = {data acquisition;geophysical image processing;remote sensing by radar;synthetic aperture radar;tropospheric electromagnetic wave propagation;reverse backprojection algorithm;SAR raw data;natural scenes;SAR image formation sibling;multistatic SAR missions;synthetic aperture radar mission concepts;geosynchronous SAR missions;observation geometry;acquisition strategy;atmospheric propagation;Synthetic aperture radar;Low earth orbit satellites;Azimuth;Atmospheric modeling;Standards;Algorithm design and analysis;Data models;Azimuth variation;backprojection algorithm;geosynchronous (GEO) SAR;raw data simulation;synthetic aperture radar (SAR);terrain observation with progressive scan (TOPS);tropospheric propagation},
    owner = {ofrey},
    
    }
    


  16. Simone Mancon, Andrea Monti Guarnieri, Davide Giudici, and Stefano Tebaldini. On the Phase Calibration by Multisquint Analysis in TOPSAR and Stripmap Interferometry. IEEE Trans. Geosci. Remote Sens., 55(1):134-147, January 2017. Keyword(s): SAR Processing, SAR Interferometry, Atmospheric modeling, Interferometry, Orbits, Spaceborne radar, Synthetic aperture radar, Target tracking, Trajectory, Calibration, TOPSAR, interferometry, multisquint phase, spaceborne, synthetic aperture radar, SAR, Spaceborne SAR.
    @Article{ManconMontiGuarnieriGiudiciTebaldiniTGRS2017PhaseCalTOPSARMultiSquint,
    author = {Simone Mancon and Andrea Monti Guarnieri and Davide Giudici and Stefano Tebaldini},
    title = {On the Phase Calibration by Multisquint Analysis in {TOPSAR} and Stripmap Interferometry},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2017},
    volume = {55},
    number = {1},
    pages = {134--147},
    month = jan,
    issn = {0196-2892},
    doi = {10.1109/TGRS.2016.2598686},
    file = {:ManconMontiGuarnieriGiudiciTebaldiniTGRS2017PhaseCalTOPSARMultiSquint.pdf:PDF},
    keywords = {SAR Processing, SAR Interferometry, Atmospheric modeling, Interferometry, Orbits, Spaceborne radar, Synthetic aperture radar, Target tracking, Trajectory, Calibration, TOPSAR, interferometry, multisquint phase, spaceborne, synthetic aperture radar, SAR, Spaceborne SAR},
    owner = {ofrey},
    
    }
    


  17. Christopher R. Mannix, David P. Belcher, and Paul S. Cannon. Measurement of Ionospheric Scintillation Parameters From SAR Images Using Corner Reflectors. IEEE Trans. Geosci. Remote Sens., 55(12):6695-6702, December 2017. Keyword(s): SAR Processin, Ionosphere, Ionospheric Scintillation, Global Positioning System, ionospheric electromagnetic wave propagation, radar imaging, radiowave propagation, synthetic aperture radar, Ascension Island, L-band, PALSAR-2, SAR PSF, SAR images, analytical theory, corner reflector, corner reflectors, ionospheric scintillation parameters, ionospheric turbulence parameters p, phase scintillation, point spread function, simultaneous GPS measurements, size 5.0 m, spotlight mode, Extraterrestrial measurements, Ionosphere, Radar tracking, Satellites, Spaceborne radar, Synthetic aperture radar, Ionosphere, ionospheric electromagnetic propagation, synthetic aperture radar.
    Abstract: Space-based low-frequency (L-band and below) synthetic aperture radar (SAR) is affected by the ionosphere. In particular, the phase scintillation causes the sidelobes to rise in a manner that can be predicted by an analytical theory of the point spread function (PSF). In this paper, the results of an experiment, in which a 5 m corner reflector on Ascension Island, was repeatedly imaged by PALSAR-2 in the spotlight mode are described. Many examples of the effect of scintillation on the SAR PSF were obtained, and all fit the theoretical model. This theoretical model of the PSF has then been used to determine two ionospheric turbulence parameters p and CkL from the SAR PSF. The values obtained have been compared with those obtained from simultaneous GPS measurements. Although the comparison shows that the two measures are strongly correlated, the differing spatial and temporal scales of SAR and GPS make exact comparison difficult.

    @Article{mannixBelcherCannonTGRS2017IonosphericScintillationFromCornerReflectors,
    author = {Christopher R. Mannix and David P. Belcher and Paul S. Cannon},
    title = {Measurement of Ionospheric Scintillation Parameters From {SAR} Images Using Corner Reflectors},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2017},
    volume = {55},
    number = {12},
    pages = {6695-6702},
    month = {Dec},
    issn = {0196-2892},
    abstract = {Space-based low-frequency (L-band and below) synthetic aperture radar (SAR) is affected by the ionosphere. In particular, the phase scintillation causes the sidelobes to rise in a manner that can be predicted by an analytical theory of the point spread function (PSF). In this paper, the results of an experiment, in which a 5 m corner reflector on Ascension Island, was repeatedly imaged by PALSAR-2 in the spotlight mode are described. Many examples of the effect of scintillation on the SAR PSF were obtained, and all fit the theoretical model. This theoretical model of the PSF has then been used to determine two ionospheric turbulence parameters p and CkL from the SAR PSF. The values obtained have been compared with those obtained from simultaneous GPS measurements. Although the comparison shows that the two measures are strongly correlated, the differing spatial and temporal scales of SAR and GPS make exact comparison difficult.},
    doi = {10.1109/TGRS.2017.2727319},
    file = {:mannixBelcherCannonTGRS2017IonosphericScintillationFromCornerReflectors.pdf:PDF},
    keywords = {SAR Processin, Ionosphere, Ionospheric Scintillation, Global Positioning System;ionospheric electromagnetic wave propagation;radar imaging;radiowave propagation;synthetic aperture radar;Ascension Island;L-band;PALSAR-2;SAR PSF;SAR images;analytical theory;corner reflector;corner reflectors;ionospheric scintillation parameters;ionospheric turbulence parameters p;phase scintillation;point spread function;simultaneous GPS measurements;size 5.0 m;spotlight mode;Extraterrestrial measurements;Ionosphere;Radar tracking;Satellites;Spaceborne radar;Synthetic aperture radar;Ionosphere;ionospheric electromagnetic propagation;synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  18. Andrea Monti Guarnieri and Fabio Rocca. Options for continuous radar Earth observations. Science China Information Sciences, 60(6), May 2017. Keyword(s): SAR Processing, geostationary, geostationary SAR, geosynchronous, geosynchronous SAR, Spaceborne SAR.
    Abstract: Near Real Time (minutes or hours) radar imaging of ground targets located anywhere on an hemisphere, with or without interferometric coherence with previous passes, can be obtained with different solutions that are considered here. Geosynchronous systems, from the one proposed in 1978 by Tomiyasu to telecom satellite compatible solutions, and Low, Medium or Geosynchronous Earth Orbit constellations are discussed. Their benefits, problems, and sizes are briefly summarized, and a comparative table is presented. If interfer-ometric coherence is requested, continuous imaging is obtained only if a very wide geostationary aperture is progressively scanned, eventually using a MIMO (Multiple Input Multiple Output) combination of several slow librating small satellites. Instead, fast librating, strip mapping, large geosynchronous satellites do provide high resolution imaging, but interferometry (and thus coherent change detection) is achievable only after a minimum delay of 12 h, i.e., when the target comes in sight without need to squint the antenna. Hence, both complex and simple systems reach full resolution interferometric imaging and thus coherent change detection capability only after 12 h.

    @Article{guarnieriRoccaSCICHINA2017OptionsForContinuousRadarEarthObservations,
    author = {Monti Guarnieri, Andrea and Rocca, Fabio},
    journal = {Science China Information Sciences},
    title = {Options for continuous radar {Earth} observations},
    year = {2017},
    month = {may},
    number = {6},
    volume = {60},
    abstract = {Near Real Time (minutes or hours) radar imaging of ground targets located anywhere on an hemisphere, with or without interferometric coherence with previous passes, can be obtained with different solutions that are considered here. Geosynchronous systems, from the one proposed in 1978 by Tomiyasu to telecom satellite compatible solutions, and Low, Medium or Geosynchronous Earth Orbit constellations are discussed. Their benefits, problems, and sizes are briefly summarized, and a comparative table is presented. If interfer-ometric coherence is requested, continuous imaging is obtained only if a very wide geostationary aperture is progressively scanned, eventually using a MIMO (Multiple Input Multiple Output) combination of several slow librating small satellites. Instead, fast librating, strip mapping, large geosynchronous satellites do provide high resolution imaging, but interferometry (and thus coherent change detection) is achievable only after a minimum delay of 12 h, i.e., when the target comes in sight without need to squint the antenna. Hence, both complex and simple systems reach full resolution interferometric imaging and thus coherent change detection capability only after 12 h.},
    doi = {10.1007/s11432-016-9067-7},
    file = {:guarnieriRoccaSCICHINA2017OptionsForContinuousRadarEarthObservations.pdf:PDF},
    keywords = {SAR Processing, geostationary, geostationary SAR, geosynchronous, geosynchronous SAR, Spaceborne SAR},
    owner = {ofrey},
    publisher = {Springer Science and Business Media {LLC}},
    
    }
    


  19. Amy L. Parker, Will E. Featherstone, Nigel T. Penna, Mick S. Filmer, and Matthew C. Garthwaite. Practical Considerations before Installing Ground-Based Geodetic Infrastructure for Integrated InSAR and cGNSS Monitoring of Vertical Land Motion. Sensors, 17(8):1-20, 2017. Keyword(s): SAR Processing, GNSS, GPS, SAR Interferometry, Integration of GNSS Networks and SAR data, Persistent Scatterer Interferometry, PSI.
    Abstract: Continuously operating Global Navigation Satellite Systems (cGNSS) can be used to convert relative values of vertical land motion (VLM) derived from Interferometric Synthetic Aperture Radar (InSAR) to absolute values in a global or regional reference frame. Artificial trihedral corner reflectors (CRs) provide high-intensity and temporally stable reflections in SAR time series imagery, more so than naturally occurring permanent scatterers. Therefore, it is logical to co-locate CRs with cGNSS as ground-based geodetic infrastructure for the integrated monitoring of VLM. We describe the practical considerations for such co-locations using four case-study examples from Perth, Australia. After basic initial considerations such as land access, sky visibility and security, temporary test deployments of co-located CRs with cGNSS should be analysed together to determine site suitability. Signal to clutter ratios from SAR imagery are used to determine potential sites for placement of the CR. A significant concern is whether the co-location of a deliberately designed reflecting object generates unwanted multipath (reflected signals) in the cGNSS data. To mitigate against this, we located CRs >30 m from the cGNSS with no inter-visibility. Daily RMS values of the zero-difference ionosphere-free carrier-phase residuals, and ellipsoidal heights from static precise point positioning GNSS processing at each co-located site were then used to ascertain that the CR did not generate unwanted cGNSS multipath. These steps form a set of recommendations for the installation of such geodetic ground-infrastructure, which may be of use to others wishing to establish integrated InSAR-cGNSS monitoring of VLM elsewhere.

    @Article{parkerEtAlSensors2017InSARandGNSSConsiderationForReflectorInstallation,
    author = {Parker, Amy L. and Featherstone, Will E. and Penna, Nigel T. and Filmer, Mick S. and Garthwaite, Matthew C.},
    title = {Practical Considerations before Installing Ground-Based Geodetic Infrastructure for Integrated {InSAR} and {cGNSS} Monitoring of Vertical Land Motion},
    journal = {Sensors},
    year = {2017},
    volume = {17},
    number = {8},
    pages = {1-20},
    issn = {1424-8220},
    abstract = {Continuously operating Global Navigation Satellite Systems (cGNSS) can be used to convert relative values of vertical land motion (VLM) derived from Interferometric Synthetic Aperture Radar (InSAR) to absolute values in a global or regional reference frame. Artificial trihedral corner reflectors (CRs) provide high-intensity and temporally stable reflections in SAR time series imagery, more so than naturally occurring permanent scatterers. Therefore, it is logical to co-locate CRs with cGNSS as ground-based geodetic infrastructure for the integrated monitoring of VLM. We describe the practical considerations for such co-locations using four case-study examples from Perth, Australia. After basic initial considerations such as land access, sky visibility and security, temporary test deployments of co-located CRs with cGNSS should be analysed together to determine site suitability. Signal to clutter ratios from SAR imagery are used to determine potential sites for placement of the CR. A significant concern is whether the co-location of a deliberately designed reflecting object generates unwanted multipath (reflected signals) in the cGNSS data. To mitigate against this, we located CRs >30 m from the cGNSS with no inter-visibility. Daily RMS values of the zero-difference ionosphere-free carrier-phase residuals, and ellipsoidal heights from static precise point positioning GNSS processing at each co-located site were then used to ascertain that the CR did not generate unwanted cGNSS multipath. These steps form a set of recommendations for the installation of such geodetic ground-infrastructure, which may be of use to others wishing to establish integrated InSAR-cGNSS monitoring of VLM elsewhere.},
    doi = {10.3390/s17081753},
    file = {:parkerEtAlSensors2017InSARandGNSSConsiderationForReflectorInstallation.pdf:PDF},
    keywords = {SAR Processing, GNSS, GPS, SAR Interferometry, Integration of GNSS Networks and SAR data, Persistent Scatterer Interferometry, PSI},
    owner = {ofrey},
    pdf = {../../../docs/parkerEtAlSensors2017InSARandGNSSConsiderationForReflectorInstallation.pdf},
    url = {http://www.mdpi.com/1424-8220/17/8/1753},
    
    }
    


  20. Achille Peternier, John Peter Merryman Boncori, and Paolo Pasquali. Near-real-time focusing of ENVISAT ASAR Stripmap and Sentinel-1 TOPS imagery exploiting OpenCL GPGPU technology. Remote Sensing of Environment, 2017. Keyword(s): SAR Processing, Synthetic Aperture Radar, Azimuth Focusing, Image Focusing, GPGPU, GPU, Graphics Processing Units, General-purpose Computing, Parallelization, OpenCL, CUDA.
    Abstract: This paper describes a SAR image focuser application exploiting General-purpose Computing On Graphics Processing Units (GPGPU), developed within the European Space Agency (ESA) funded SARIPA project. Instead of relying on distributed technologies, such as clustering or High-performance Computing (HPC), the SARIPA processor is designed to run on a single computer equipped with multiple GPUs. To exploit the computational power of the latter, while retaining a high level of hardware portability, SARIPA is written using the Open Computing Language (OpenCL) framework rather than the more widespread Compute Unified Device Architecture (CUDA). This allows the application to exploit both GPUs and CPUs without requiring any code modification or duplication. A further level of optimization is achieved thanks to a software architecture, which mimics a distributed computing environment, although implemented on a single machine. SARIPA's performance is demonstrated on ENVISAT ASAR Stripmap imagery, for which a real-time performance of 8.5s is achieved, and on Sentinel-1 Interferometric Wideswath (IW) raw data products, for which a near-real time processing time of about 1min is required. Such a performance has the potential of significantly reducing the storage requirements for wide-area monitoring applications, by avoiding the need of maintaining large permanent archives of Level 1 (focused) imagery, in favor of lighter Level 0 (raw) products, which can be focused on-the-fly within the user's application processing pipelines at almost no overhead.

    @Article{peternierMerrymanPasqualiRSE2017GPUNearRealTimeAzimuthFocusingSARIPA,
    author = {Peternier, Achille and Merryman Boncori, John Peter and Pasquali, Paolo},
    title = {Near-real-time focusing of {ENVISAT} {ASAR} Stripmap and {Sentinel-1} {TOPS} imagery exploiting {OpenCL} {GPGPU} technology},
    journal = {Remote Sensing of Environment},
    year = {2017},
    issn = {0034-4257},
    abstract = {This paper describes a SAR image focuser application exploiting General-purpose Computing On Graphics Processing Units (GPGPU), developed within the European Space Agency (ESA) funded SARIPA project. Instead of relying on distributed technologies, such as clustering or High-performance Computing (HPC), the SARIPA processor is designed to run on a single computer equipped with multiple GPUs. To exploit the computational power of the latter, while retaining a high level of hardware portability, SARIPA is written using the Open Computing Language (OpenCL) framework rather than the more widespread Compute Unified Device Architecture (CUDA). This allows the application to exploit both GPUs and CPUs without requiring any code modification or duplication. A further level of optimization is achieved thanks to a software architecture, which mimics a distributed computing environment, although implemented on a single machine. SARIPA's performance is demonstrated on ENVISAT ASAR Stripmap imagery, for which a real-time performance of 8.5s is achieved, and on Sentinel-1 Interferometric Wideswath (IW) raw data products, for which a near-real time processing time of about 1min is required. Such a performance has the potential of significantly reducing the storage requirements for wide-area monitoring applications, by avoiding the need of maintaining large permanent archives of Level 1 (focused) imagery, in favor of lighter Level 0 (raw) products, which can be focused on-the-fly within the user's application processing pipelines at almost no overhead.},
    doi = {http://dx.doi.org/10.1016/j.rse.2017.04.006},
    file = {:peternierMerrymanPasqualiRSE2017GPUNearRealTimeAzimuthFocusingSARIPA.pdf:PDF},
    keywords = {SAR Processing, Synthetic Aperture Radar, Azimuth Focusing, Image Focusing, GPGPU, GPU, Graphics Processing Units, General-purpose Computing, Parallelization,OpenCL, CUDA},
    owner = {ofrey},
    pdf = {../../../docs/peternierMerrymanPasqualiRSE2017GPUNearRealTimeAzimuthFocusingSARIPA.pdf},
    url = {http://www.sciencedirect.com/science/article/pii/S0034425717301554},
    
    }
    


  21. M. Pieraccini and L. Miccinesi. ArcSAR: Theory, Simulations, and Experimental Verification. IEEE Transactions on Microwave Theory and Techniques, 65(1):293-301, January 2017. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, radar imaging, synthetic aperture radar, 3D space, ArcSAR images, antenna movement, defocusing effect, ground-based synthetic aperture radar, image synthesis, linear rail, spatial diversity, Apertures, Radar antennas, Radar imaging, Spaceborne radar, Synthetic aperture radar, Ground-based synthetic aperture radar (GBSAR), GBSAR, terrestrial radar, terrestrial SAR, radar, remote sensing, synthetic aperture radar (SAR).
    Abstract: ArcSAR is a ground-based synthetic aperture radar (GBSAR) that has recently been receiving increasing interest in the scientific literature. While the conventional GBSAR exploits the movement of an antenna along a linear rail to synthesize a large aperture, an ArcSAR exploits the spatial diversity of the data acquired by an antenna fixed to a rotating arm. The great advantage of ArcSAR is its capability to synthesize images at 360 deg with a constant resolution in azimuth. In this paper, the authors propose and test a new focusing algorithm that does not require to operate in the far field and neither with narrow beam antennas; moreover, it is flexible enough to focus on any plane (not necessarily on the rotation plane) as well as in the whole 3-D space. Furthermore, the authors demonstrate theoretically and experimentally that ArcSAR images can be affected by a ?defocusing effect? of the targets far from the rotation plane, which has to be taken into consideration when designing such radars.

    @Article{pieracciniMiccinesiTMTT2017ARCSARBGSAR,
    author = {M. Pieraccini and L. Miccinesi},
    journal = {IEEE Transactions on Microwave Theory and Techniques},
    title = {ArcSAR: Theory, Simulations, and Experimental Verification},
    year = {2017},
    issn = {0018-9480},
    month = jan,
    number = {1},
    pages = {293-301},
    volume = {65},
    abstract = {ArcSAR is a ground-based synthetic aperture radar (GBSAR) that has recently been receiving increasing interest in the scientific literature. While the conventional GBSAR exploits the movement of an antenna along a linear rail to synthesize a large aperture, an ArcSAR exploits the spatial diversity of the data acquired by an antenna fixed to a rotating arm. The great advantage of ArcSAR is its capability to synthesize images at 360 deg with a constant resolution in azimuth. In this paper, the authors propose and test a new focusing algorithm that does not require to operate in the far field and neither with narrow beam antennas; moreover, it is flexible enough to focus on any plane (not necessarily on the rotation plane) as well as in the whole 3-D space. Furthermore, the authors demonstrate theoretically and experimentally that ArcSAR images can be affected by a ?defocusing effect? of the targets far from the rotation plane, which has to be taken into consideration when designing such radars.},
    
    
     doi = {10.1109/TMTT.2016.2613926},
    file = {:pieracciniMiccinesiTMTT2017ARCSARBGSAR.pdf:PDF},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,radar imaging;synthetic aperture radar;3D space;ArcSAR images;antenna movement;defocusing effect;ground-based synthetic aperture radar;image synthesis;linear rail;spatial diversity;Apertures;Radar antennas;Radar imaging;Spaceborne radar;Synthetic aperture radar;Ground-based synthetic aperture radar (GBSAR);GBSAR,terrestrial radar, terrestrial SAR,radar;remote sensing;synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  22. Badreddine Rekioua, Matthieu Davy, Laurent Ferro-Famil, and Stefano Tebaldini. Snowpack permittivity profile retrieval from tomographic SAR data. Comptes Rendus Physique, 18(1):57-65, 2017. Keyword(s): Snowpack, snow permittivity, SAR, SAR tomography, GB-SAR, ground-based SAR, Time-domain back-projection, TDBP.
    Abstract: This work deals with 3D structure characterisation and permittivity profile retrieval of snowpacks by tomographic SAR data processing. The acquisition system is a very high resolution ground based SAR system, developed and operated by the SAPHIR team, of IETR, University of Rennes-1 (France). It consists mainly of a vector network analyser and a multi-static antenna system, moving along two orthogonal directions, so as to obtain a two-dimensional synthetic array. Data were acquired during the AlpSAR campaign carried by the European Space Agency and led by ENVEO. In this study, tomographic imaging is performed using Time Domain Back Projection and consists in coherently combining the different recorded backscatter contributions. The assumption of free-space propagation during the focusing process is discussed and illustrated by focusing experimental data. An iterative method for estimating true refractive indices of the snow layers is presented. The antenna pattern is also compensated for. The obtained tomograms after refractive index correction are compared to the stratigraphy of the observed snowpack.

    @Article{rekiouaDavyFerroFamilTebaldini2017SnowTomography,
    author = {Badreddine Rekioua and Matthieu Davy and Laurent Ferro-Famil and Stefano Tebaldini},
    journal = {Comptes Rendus Physique},
    title = {Snowpack permittivity profile retrieval from tomographic {SAR} data},
    year = {2017},
    issn = {1631-0705},
    number = {1},
    pages = {57-65},
    volume = {18},
    abstract = {This work deals with 3D structure characterisation and permittivity profile retrieval of snowpacks by tomographic SAR data processing. The acquisition system is a very high resolution ground based SAR system, developed and operated by the SAPHIR team, of IETR, University of Rennes-1 (France). It consists mainly of a vector network analyser and a multi-static antenna system, moving along two orthogonal directions, so as to obtain a two-dimensional synthetic array. Data were acquired during the AlpSAR campaign carried by the European Space Agency and led by ENVEO. In this study, tomographic imaging is performed using Time Domain Back Projection and consists in coherently combining the different recorded backscatter contributions. The assumption of free-space propagation during the focusing process is discussed and illustrated by focusing experimental data. An iterative method for estimating true refractive indices of the snow layers is presented. The antenna pattern is also compensated for. The obtained tomograms after refractive index correction are compared to the stratigraphy of the observed snowpack.},
    doi = {http://dx.doi.org/10.1016/j.crhy.2015.12.016},
    file = {:rekiouaDavyFerroFamilTebaldini2017SnowTomography.pdf:PDF},
    keywords = {Snowpack,snow permittivity, SAR, SAR tomography, GB-SAR, ground-based SAR, Time-domain back-projection, TDBP},
    owner = {ofrey},
    pdf = {../../../docs/rekiouaDavyFerroFamilTebaldini2017SnowTomography.pdf},
    url = {http://www.sciencedirect.com/science/article/pii/S1631070515002947},
    
    }
    


  23. Zahra Sadeghi, Mohammad Javad Valadan Zoej, and Jan-Peter Muller. Combination of Persistent Scatterer Interferometry and Single-Baseline Polarimetric Coherence Optimisation to Estimate Deformation Rates with Application to Tehran Basin. PFG -- Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85(5):327-340, December 2017.
    Abstract: This study reports on the monitoring of land subsidence in a rural area located in the southwest of the Tehran basin, Iran, by combining a persistent scatterer interferometry (PSI) method with a single-baseline polarimetric coherence optimisation. Owing to vegetation coverage in this rural area, coherence level experiences a decline and the performance and coverage of conventional interferometry to estimate deformation rate reduces concomitantly. Since the launch of satellites with polarimetric information, the polarimetric InSAR (PolInSAR) technique, which is vector interferometry with different polarimetric channels, has been introduced to optimise the coherence level. One of the most common criteria to select PS pixels is coherence and maximising the coherence can lead to an increased number of selected PS pixels and enhanced PSI performance. The single-baseline polarimetric coherence optimisation method assumes equal polarisation states at the end of each baseline. In order to apply this technique in our study, two different multi-look windows for coherence calculation and also two TerraSAR-X data sets with different numbers of images are used to assess their effect on the polarimetric PSI. Combination of the single-baseline coherence optimisation method with PSI shows significant improvements (more than 50{\%}) in terms of the number of selected PS pixels in the case study even using a data set with a small number of images. A 15 x 15 multi-look window selects a greater number of PS pixels compared to a 9 x 9 multi-look window, although this entails reducing spatial resolution. The most effective PSI approach in terms of the density of the selected PS turned out to be polarimetric PSI using a data set with a large number of images and a selection of a 15 x 15 multi-look window. Validation of the PSI methods using a large number of images with 9 x 9 and 15 x 15 multi-look windows via levelling measurements confirms the accuracy and reliability of the results obtained.

    @Article{sadeghiValadanZoejMullerPFG2017PSInSARPolarimetricCoherenceOptimisation,
    author = {Sadeghi, Zahra and Valadan Zoej, Mohammad Javad and Muller, Jan-Peter},
    title = {Combination of Persistent Scatterer Interferometry and Single-Baseline Polarimetric Coherence Optimisation to Estimate Deformation Rates with Application to {T}ehran Basin},
    journal = {PFG -- Journal of Photogrammetry, Remote Sensing and Geoinformation Science},
    year = {2017},
    volume = {85},
    number = {5},
    pages = {327--340},
    month = dec,
    issn = {2512-2819},
    abstract = {This study reports on the monitoring of land subsidence in a rural area located in the southwest of the Tehran basin, Iran, by combining a persistent scatterer interferometry (PSI) method with a single-baseline polarimetric coherence optimisation. Owing to vegetation coverage in this rural area, coherence level experiences a decline and the performance and coverage of conventional interferometry to estimate deformation rate reduces concomitantly. Since the launch of satellites with polarimetric information, the polarimetric InSAR (PolInSAR) technique, which is vector interferometry with different polarimetric channels, has been introduced to optimise the coherence level. One of the most common criteria to select PS pixels is coherence and maximising the coherence can lead to an increased number of selected PS pixels and enhanced PSI performance. The single-baseline polarimetric coherence optimisation method assumes equal polarisation states at the end of each baseline. In order to apply this technique in our study, two different multi-look windows for coherence calculation and also two TerraSAR-X data sets with different numbers of images are used to assess their effect on the polarimetric PSI. Combination of the single-baseline coherence optimisation method with PSI shows significant improvements (more than 50{\%}) in terms of the number of selected PS pixels in the case study even using a data set with a small number of images. A 15 x 15 multi-look window selects a greater number of PS pixels compared to a 9 x 9 multi-look window, although this entails reducing spatial resolution. The most effective PSI approach in terms of the density of the selected PS turned out to be polarimetric PSI using a data set with a large number of images and a selection of a 15 x 15 multi-look window. Validation of the PSI methods using a large number of images with 9 x 9 and 15 x 15 multi-look windows via levelling measurements confirms the accuracy and reliability of the results obtained.},
    day = {01},
    doi = {10.1007/s41064-017-0030-3},
    url = {https://doi.org/10.1007/s41064-017-0030-3},
    
    }
    


  24. Zahra Sadeghi, M. J. Valadan Zoej, and J. P. Muller. Monitoring Land Subsidence in a Rural Area Using a Combination of ADInSAR and Polarimetric Coherence Optimization. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(8):3582-3590, August 2017. Keyword(s): environmental monitoring (geophysics), geomorphology, optimisation, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, MCPO, North Iran, Tehran basin, TerraSAR-X images, agricultural fields, coherence-set based polarimetry optimization, coherent pixel density, differential synthetic aperture radar interferometry, land subsidence monitoring, modified coherence set-based polarimetry optimization, pixel phase quality, polarimetric ADInSAR, polarimetric DInSAR, polarimetric coherence optimization, rural area, satellites, search polarimetry optimization, single-baseline coherence optimization method, single-baseline coherence optimization technique, Coherence, Interferometry, Optimization methods, Polarimetry, Synthetic aperture radar, Advanced differential synthetic aperture radar interferometry (ADInSAR), coherence optimization, polarimetric differential synthetic aperture radar interferometry (DInSAR), polarimetry.
    Abstract: This paper investigates a combination of advanced differential synthetic aperture radar interferometry (ADInSAR) with different coherence optimization methods. After the launch of satellites with polarimetry capabilities, differential synthetic aperture radar interferometry (DInSAR) is feasible to generate polarimetric DInSAR to enhance pixel phase quality and increase coherent pixel (CP) density. The first method proposed in this paper, modified coherence set-based polarimetry optimization (MCPO), is a modification of a known single-baseline coherence optimization method to optimize coherence of all interferograms simultaneously. The second method, coherence-set based polarimetry optimization (CPO), was presented by Neumann et al., and is an existing revision of the single-baseline coherence optimization technique. The final method, exhaustive search polarimetry optimization, is a search-based approach to find the optimized scattering mechanism introduced by Navarro-Sanchez et al. The case study is the Tehran basin located in the North of Iran, which suffers from a high-rate of land subsidence and is covered by agricultural fields. Usually such an area would significantly decorrelate but applying polarimetric ADInSAR allows us to obtain a more CP coverage. A set of dual polarization TerraSAR-X images with 9x9 and 15 x 15 as multilook factors were used within the polarimetric ADInSAR procedure. All three coherence optimization methods with two different multilook factors are shown to have increased the density and phase quality of CPs. Moreover, the estimated deformation rates were evaluated using available levelling measurements. MCPO, which is presented in this paper, works more successful than CPO in terms of CPs density, phase quality and deformation accuracy.

    @Article{sadeghiValadanZoejMullerJSTARSDInSARandPolarimetricCoherenceOptimization,
    author = {Sadeghi, Zahra and Valadan Zoej, M. J. and Muller, J. P.},
    title = {Monitoring Land Subsidence in a Rural Area Using a Combination of {ADInSAR} and Polarimetric Coherence Optimization},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2017},
    volume = {10},
    number = {8},
    pages = {3582-3590},
    month = aug,
    issn = {1939-1404},
    abstract = {This paper investigates a combination of advanced differential synthetic aperture radar interferometry (ADInSAR) with different coherence optimization methods. After the launch of satellites with polarimetry capabilities, differential synthetic aperture radar interferometry (DInSAR) is feasible to generate polarimetric DInSAR to enhance pixel phase quality and increase coherent pixel (CP) density. The first method proposed in this paper, modified coherence set-based polarimetry optimization (MCPO), is a modification of a known single-baseline coherence optimization method to optimize coherence of all interferograms simultaneously. The second method, coherence-set based polarimetry optimization (CPO), was presented by Neumann et al., and is an existing revision of the single-baseline coherence optimization technique. The final method, exhaustive search polarimetry optimization, is a search-based approach to find the optimized scattering mechanism introduced by Navarro-Sanchez et al. The case study is the Tehran basin located in the North of Iran, which suffers from a high-rate of land subsidence and is covered by agricultural fields. Usually such an area would significantly decorrelate but applying polarimetric ADInSAR allows us to obtain a more CP coverage. A set of dual polarization TerraSAR-X images with 9x9 and 15 x 15 as multilook factors were used within the polarimetric ADInSAR procedure. All three coherence optimization methods with two different multilook factors are shown to have increased the density and phase quality of CPs. Moreover, the estimated deformation rates were evaluated using available levelling measurements. MCPO, which is presented in this paper, works more successful than CPO in terms of CPs density, phase quality and deformation accuracy.},
    doi = {10.1109/JSTARS.2017.2689823},
    keywords = {environmental monitoring (geophysics);geomorphology;optimisation;radar interferometry;radar polarimetry;remote sensing by radar;synthetic aperture radar;MCPO;North Iran;Tehran basin;TerraSAR-X images;agricultural fields;coherence-set based polarimetry optimization;coherent pixel density;differential synthetic aperture radar interferometry;land subsidence monitoring;modified coherence set-based polarimetry optimization;pixel phase quality;polarimetric ADInSAR;polarimetric DInSAR;polarimetric coherence optimization;rural area;satellites;search polarimetry optimization;single-baseline coherence optimization method;single-baseline coherence optimization technique;Coherence;Interferometry;Optimization methods;Polarimetry;Synthetic aperture radar;Advanced differential synthetic aperture radar interferometry (ADInSAR);coherence optimization;polarimetric differential synthetic aperture radar interferometry (DInSAR), polarimetry},
    owner = {ofrey},
    
    }
    


  25. Tazio Strozzi, Rafael Caduff, Urs Wegmuller, Hugo Raetzo, and Marc Hauser. Widespread surface subsidence measured with satellite SAR interferometry in the Swiss alpine range associated with the construction of the Gotthard Base Tunnel. Remote Sensing of Environment, 190:1 - 12, 2017. Keyword(s): SAR interferometry, Tunnel, Surface subsidence, Landslides.
    Abstract: Abstract Drilling deep tunnels in alpine rocks might induce surface settlements of a few centimetres because of groundwater drainage and associated pore pressure reduction. Settlements of this order of magnitude are sufficient to pose a potential threat to the integrity of any large concrete structure such as arch dams located above the tunnel and an accurate survey of surface deformation before, during and after construction is of high importance. We present the spatial and temporal evolution of surface subsidence measured with satellite SAR interferometry associated with the construction of the 57km long Gotthard Base Tunnel in Switzerland. Significant deformations of 1 to 12mm/year were detected between 2003 and 2010 with ENVISAT ASAR data above the tunnel on villages and sparsely vegetated alpine slopes where no displacement was recorded between 1992 and 2000 with ERS-1/2 SAR data. Our results, available also for sectors where there is no information from any other surveying technique, are important not only to assess the hazard posed on any large concrete structure but also for the development and calibration of numerical models - to be employed to simulate the expected surface deformation before and during the construction works - and to study the effect of groundwater drainage on the dynamic of large deep-seated landslides.

    @Article{strozziCaduffWegmullerRaetzoHauserRSE2017,
    author = {Tazio Strozzi and Rafael Caduff and Urs Wegmuller and Hugo Raetzo and Marc Hauser},
    title = {Widespread surface subsidence measured with satellite {SAR} interferometry in the {Swiss} alpine range associated with the construction of the {Gotthard} {Base} {Tunnel}},
    journal = {Remote Sensing of Environment},
    year = {2017},
    volume = {190},
    pages = {1 - 12},
    issn = {0034-4257},
    abstract = {Abstract Drilling deep tunnels in alpine rocks might induce surface settlements of a few centimetres because of groundwater drainage and associated pore pressure reduction. Settlements of this order of magnitude are sufficient to pose a potential threat to the integrity of any large concrete structure such as arch dams located above the tunnel and an accurate survey of surface deformation before, during and after construction is of high importance. We present the spatial and temporal evolution of surface subsidence measured with satellite SAR interferometry associated with the construction of the 57km long Gotthard Base Tunnel in Switzerland. Significant deformations of 1 to 12mm/year were detected between 2003 and 2010 with ENVISAT ASAR data above the tunnel on villages and sparsely vegetated alpine slopes where no displacement was recorded between 1992 and 2000 with ERS-1/2 SAR data. Our results, available also for sectors where there is no information from any other surveying technique, are important not only to assess the hazard posed on any large concrete structure but also for the development and calibration of numerical models - to be employed to simulate the expected surface deformation before and during the construction works - and to study the effect of groundwater drainage on the dynamic of large deep-seated landslides.},
    doi = {https://doi.org/10.1016/j.rse.2016.12.007},
    file = {:strozziCaduffWegmullerRaetzoHauserRSE2017.pdf:PDF},
    keywords = {SAR interferometry, Tunnel, Surface subsidence, Landslides},
    url = {http://www.sciencedirect.com/science/article/pii/S0034425716304795},
    
    }
    


  26. S. A. V. Synnes, A. J. Hunter, Roy E. Hansen, T. O. Saebo, H. J. Callow, R. van Vossen, and A. Austeng. Wideband Synthetic Aperture Sonar Backprojection With Maximization of Wave Number Domain Support. IEEE Journal of Oceanic Engineering, 42(4):880-891, October 2017. Keyword(s): Synthetic Aperture Sonar, SAS, image filtering, image resolution, optimisation, sensor arrays, sonar imaging, synthetic aperture sonar, time-domain analysis, BP, SAS arrays, SAS image formation algorithms, TDBP access data, WD filtering, aspect-dependent scattering, data degradation, frequency-dependent scattering, generic SAS design, sensor data quality, spatial domain quality metrics, time domain backprojection access data, wave number domain counterpart, wave number domain support maximization, wideband SAS systems, wideband synthetic aperture sonar backprojection, widebeam synthetic aperture sonar backprojection, Image resolution, Imaging, Performance evaluation, Scattering, Sonar applications, Synthetic aperture sonar, Wideband, Along-track ambiguity, backprojection (BP) algorithm, grating lobes, synthetic aperture sonar (SAS), wideband sonar.
    Abstract: Wideband and widebeam synthetic aperture sonar (SAS) can provide information on the frequency- and aspect-dependent scattering in a scene. We suggest an approach to predict the quality of the sensor data over the available frequencies and aspect angles. We relate the typical spatial domain quality metrics to their wave number domain (WD) counterpart, and use these to map the data quality in WD. Because SAS arrays often are undersampled along-track, we pay particular attention to data degradation from aliasing. We use the proposed approach to examine how three SAS image formation algorithms based on time domain backprojection (TDBP) access data of different quality from wideband SAS systems. We illustrate the results with predictions for a generic SAS design and demonstrate the findings on two experimental systems. We observe that the maximum support of high-quality data is achieved through BP onto a high-resolution grid followed by WD filtering.

    @Article{synnesHunterHansenSaeboCallowVanVossenAustengJOE2017WidebandSyntheticApertureSonarBackprojection,
    author = {S. A. V. Synnes and A. J. Hunter and Roy E. Hansen and T. O. Saebo and H. J. Callow and R. van Vossen and A. Austeng},
    title = {Wideband Synthetic Aperture Sonar Backprojection With Maximization of Wave Number Domain Support},
    journal = {IEEE Journal of Oceanic Engineering},
    year = {2017},
    volume = {42},
    number = {4},
    pages = {880-891},
    month = {Oct},
    issn = {0364-9059},
    abstract = {Wideband and widebeam synthetic aperture sonar (SAS) can provide information on the frequency- and aspect-dependent scattering in a scene. We suggest an approach to predict the quality of the sensor data over the available frequencies and aspect angles. We relate the typical spatial domain quality metrics to their wave number domain (WD) counterpart, and use these to map the data quality in WD. Because SAS arrays often are undersampled along-track, we pay particular attention to data degradation from aliasing. We use the proposed approach to examine how three SAS image formation algorithms based on time domain backprojection (TDBP) access data of different quality from wideband SAS systems. We illustrate the results with predictions for a generic SAS design and demonstrate the findings on two experimental systems. We observe that the maximum support of high-quality data is achieved through BP onto a high-resolution grid followed by WD filtering.},
    doi = {10.1109/JOE.2016.2614717},
    file = {:synnesHunterHansenSaeboCallowVanVossenAustengJOE2017WidebandSyntheticApertureSonarBackprojection.pdf:PDF},
    keywords = {Synthetic Aperture Sonar, SAS,image filtering;image resolution;optimisation;sensor arrays;sonar imaging;synthetic aperture sonar;time-domain analysis;BP;SAS arrays;SAS image formation algorithms;TDBP access data;WD filtering;aspect-dependent scattering;data degradation;frequency-dependent scattering;generic SAS design;sensor data quality;spatial domain quality metrics;time domain backprojection access data;wave number domain counterpart;wave number domain support maximization;wideband SAS systems;wideband synthetic aperture sonar backprojection;widebeam synthetic aperture sonar backprojection;Image resolution;Imaging;Performance evaluation;Scattering;Sonar applications;Synthetic aperture sonar;Wideband;Along-track ambiguity;backprojection (BP) algorithm;grating lobes;synthetic aperture sonar (SAS);wideband sonar},
    
    }
    


  27. H. Yu, Y. Lan, J. Xu, D. An, and Hyonki Lee. Large-Scale ${L}^{0}$ -Norm and ${L}^{1}$ -Norm 2-D Phase Unwrapping. IEEE Transactions on Geoscience and Remote Sensing, 55(8):4712-4728, August 2017. Keyword(s): SAR Processing, Phase Unwrapping, radar interferometry, remote sensing by radar, signal processing, synthetic aperture radar, InSAR technology, L0-norm 2D phase unwrapping, L1-norm 2D phase unwrapping, L1-norm envelope-sparsity theorem, big-data, computer hardware, global L1-norm PU solution, local L1-norm PU solution, subinterferograms, synthetic aperture radar interferometry, tiling accuracy, tiling resolution, tiling strategy, Hardware, Laser radar, Laser theory, Memory management, Optimization, Spatial resolution, Synthetic aperture radar interferometry, 2-D phase unwrapping (PU), L1-norm, L0-norm, large scale, synthetic aperture radar interferometry (InSAR), tiling strategy.
    Abstract: Two-dimensional phase unwrapping (PU) is a crucial processing step of synthetic aperture radar interferometry (InSAR). With the rapid advance of InSAR technology, the scale of interferograms is becoming increasingly larger. When the size of the input interferogram exceeds computer hardware capabilities, PU becomes more problematic in terms of computational and memory requirements. In the case of ?big-data? PU, the input interferogram needs to be first tiled into a number of subinterferograms, unwrapped separately, and then spliced together. Hence, whether the PU result of each subinterferogram is consistent with that of the whole interferogram is critical to the large-scale PU process. To effectively solve this problem, the L1-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L1-norm PU solutions, is put forward and proved. Furthermore, the L0-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L0-norm PU solutions, is also proposed and proved. Afterward, based on these two theorems, two tiling strategies are put forward for the large-scale L0-norm and L1-norm PU methods. In addition, this paper presents the concepts of the tiling accuracy and the tiling resolution, which are the criteria used to evaluate the effectiveness of a tiling strategy, and we use them to quantitatively analyze the aforementioned tiling strategies. Both theoretical analysis and experimental results show that the proposed tiling strategies are effective for the largescale L0-norm and L1-norm PU problems.

    @Article{yuLanXuAnLeeTGRS2017L1NormL0Norm2DPhaseUnwrapping,
    author = {H. Yu and Y. Lan and J. Xu and D. An and Hyonki Lee},
    title = {Large-Scale ${L}^{0}$ -Norm and ${L}^{1}$ -Norm {2-D} Phase Unwrapping},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2017},
    volume = {55},
    number = {8},
    month = {Aug},
    pages = {4712-4728},
    issn = {0196-2892},
    doi = {10.1109/TGRS.2017.2698452},
    abstract = {Two-dimensional phase unwrapping (PU) is a crucial processing step of synthetic aperture radar interferometry (InSAR). With the rapid advance of InSAR technology, the scale of interferograms is becoming increasingly larger. When the size of the input interferogram exceeds computer hardware capabilities, PU becomes more problematic in terms of computational and memory requirements. In the case of ?big-data? PU, the input interferogram needs to be first tiled into a number of subinterferograms, unwrapped separately, and then spliced together. Hence, whether the PU result of each subinterferogram is consistent with that of the whole interferogram is critical to the large-scale PU process. To effectively solve this problem, the L1-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L1-norm PU solutions, is put forward and proved. Furthermore, the L0-norm envelope-sparsity theorem, which gives a sufficient condition to exactly guarantee the consistency between local and global L0-norm PU solutions, is also proposed and proved. Afterward, based on these two theorems, two tiling strategies are put forward for the large-scale L0-norm and L1-norm PU methods. In addition, this paper presents the concepts of the tiling accuracy and the tiling resolution, which are the criteria used to evaluate the effectiveness of a tiling strategy, and we use them to quantitatively analyze the aforementioned tiling strategies. Both theoretical analysis and experimental results show that the proposed tiling strategies are effective for the largescale L0-norm and L1-norm PU problems.},
    keywords = {SAR Processing, Phase Unwrapping, radar interferometry;remote sensing by radar;signal processing;synthetic aperture radar;InSAR technology;L0-norm 2D phase unwrapping;L1-norm 2D phase unwrapping;L1-norm envelope-sparsity theorem;big-data;computer hardware;global L1-norm PU solution;local L1-norm PU solution;subinterferograms;synthetic aperture radar interferometry;tiling accuracy;tiling resolution;tiling strategy;Hardware;Laser radar;Laser theory;Memory management;Optimization;Spatial resolution;Synthetic aperture radar interferometry;2-D phase unwrapping (PU);L1-norm;L0-norm;large scale;synthetic aperture radar interferometry (InSAR);tiling strategy},
    owner = {ofrey},
    
    }
    


  28. S. Zhou, L. Yang, L. Zhao, and G. Bi. Quasi-Polar-Based FFBP Algorithm for Miniature UAV SAR Imaging Without Navigational Data. IEEE Transactions on Geoscience and Remote Sensing, 55(12):7053-7065, December 2017. Keyword(s): autonomous aerial vehicles, image resolution, radar imaging, radar resolution, synthetic aperture radar, polar coordinate system, phase autofocusing, trajectory deviations, quasipolar grid image, data-driven motion compensation, back-projection algorithm, unmanned aerial vehicle synthetic aperture radar applications, time-domain algorithms, trajectory designation, flexible geometric configuration, navigational data, miniature UAV SAR imaging, FFBP algorithm, miniature UAV-SAR test bed, raw data experiments, high-resolution SAR applications, image focusing quality, analytical image spectrum, phase errors, quasipolar coordinate system, Synthetic aperture radar, Trajectory, Unmanned aerial vehicles, Signal processing algorithms, Algorithm design and analysis, Fast factorized back-projection (FFBP), motion compensation (MOCO), quasi-polar coordinate system, synthetic aperture radar (SAR), unmanned aerial vehicle (UAV).
    Abstract: Because of flexible geometric configuration and trajectory designation, time-domain algorithms become popular for unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) applications. In this paper, a new quasi-polar-coordinate-based fast factorized back-projection (FFBP) algorithm combined with data-driven motion compensation is proposed for miniature UAV-SAR imaging. By utilizing wavenumber decomposition, the analytical spectrum of a quasi-polar grid image is obtained, where the phase errors arising from the trajectory deviations can be conveniently investigated and the phase autofocusing can be compatibly incorporated. Different from the conventional FFBP based on a polar coordinate system, the proposed algorithm operates in a quasi-polar coordinate system, where the phase errors become spacial invariant and can be accurately estimated and easily compensated. Moreover, the relationship between phase errors and nonsystematic range cell migration (NsRCM) is revealed according to the analytical image spectrum, based on which the NsRCM correction is developed to further improve the image focusing quality for high-resolution SAR applications. Promising experimental results from the raw data experiments of miniature UAV-SAR test bed are presented and analyzed to validate the advantages of the proposed algorithm.

    @Article{zhouYangZhaoBiTGRS2017QuasiPolarFFBPforMiniatureUAVbasedSARImagingWithoutNavigationData,
    author = {S. {Zhou} and L. {Yang} and L. {Zhao} and G. {Bi}},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {Quasi-Polar-Based {FFBP} Algorithm for Miniature {UAV} SAR Imaging Without Navigational Data},
    year = {2017},
    issn = {1558-0644},
    month = dec,
    number = {12},
    pages = {7053-7065},
    volume = {55},
    abstract = {Because of flexible geometric configuration and trajectory designation, time-domain algorithms become popular for unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) applications. In this paper, a new quasi-polar-coordinate-based fast factorized back-projection (FFBP) algorithm combined with data-driven motion compensation is proposed for miniature UAV-SAR imaging. By utilizing wavenumber decomposition, the analytical spectrum of a quasi-polar grid image is obtained, where the phase errors arising from the trajectory deviations can be conveniently investigated and the phase autofocusing can be compatibly incorporated. Different from the conventional FFBP based on a polar coordinate system, the proposed algorithm operates in a quasi-polar coordinate system, where the phase errors become spacial invariant and can be accurately estimated and easily compensated. Moreover, the relationship between phase errors and nonsystematic range cell migration (NsRCM) is revealed according to the analytical image spectrum, based on which the NsRCM correction is developed to further improve the image focusing quality for high-resolution SAR applications. Promising experimental results from the raw data experiments of miniature UAV-SAR test bed are presented and analyzed to validate the advantages of the proposed algorithm.},
    doi = {10.1109/TGRS.2017.2739133},
    file = {:zhouYangZhaoBiTGRS2017QuasiPolarFFBPforMiniatureUAVbasedSARImagingWithoutNavigationData.pdf:PDF},
    keywords = {autonomous aerial vehicles;image resolution;radar imaging;radar resolution;synthetic aperture radar;polar coordinate system;phase autofocusing;trajectory deviations;quasipolar grid image;data-driven motion compensation;back-projection algorithm;unmanned aerial vehicle synthetic aperture radar applications;time-domain algorithms;trajectory designation;flexible geometric configuration;navigational data;miniature UAV SAR imaging;FFBP algorithm;miniature UAV-SAR test bed;raw data experiments;high-resolution SAR applications;image focusing quality;analytical image spectrum;phase errors;quasipolar coordinate system;Synthetic aperture radar;Trajectory;Unmanned aerial vehicles;Signal processing algorithms;Algorithm design and analysis;Fast factorized back-projection (FFBP);motion compensation (MOCO);quasi-polar coordinate system;synthetic aperture radar (SAR);unmanned aerial vehicle (UAV)},
    owner = {ofrey},
    
    }
    


Conference articles

  1. Ning Cao, Hyongki Lee, Evan Zaugg, Ramesh Shrestha, William E. Carter, Craig Glennie, Zhong Lu, and Juan Carlos Fernandez Diaz. Evaluation of an airborne SAR system for deformation mapping: A case study over the slumgullion landslide. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 1684-1687, July 2017. Keyword(s): SAR Processing, Interferometry, SAR Interferometry, InSAR, Differential SAR Interferometry, DInSAR, Repeat-Pass Interferometry, deformation monitoring, subsidence monitoring, Displacement, Earth, Global Positioning System, Laser radar, Spaceborne radar, Strain, Synthetic aperture radar, Terrain factors, GPS, InSAR, Landslide, LiDAR, SAR.
    Abstract: In this study, we present a case study of the Slumgullion landslide conducted in July 2015 to demonstrate the feasibility of deformation mapping with an airborne synthetic aperture radar (SAR) system known as ARTEMIS SlimSAR, which is a compact, modular, and multi-frequency radar system. For this study, the L-band SlimSAR was installed on a Cessna 206 aircraft and data were collected on July 3, 7, and 10 of 2015 and processed using the time-domain backprojection algorithm. Airborne light detection and ranging (LiDAR) campaign, GPS surveys and spaceborne InSAR analysis using COSMO-SkyMed images were also conducted to verify the performance of the airborne SAR system. The airborne InSAR results showed satisfying agreement with the GPS and spaceborne InSAR results. A 3-D deformation map over Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topography.

    @InProceedings{caoLeeZauggShresthaCarterGlennieLuDiazIGARSS2017TDBPAirborneDInSAR,
    author = {Cao, Ning and Lee, Hyongki and Zaugg, Evan and Shrestha, Ramesh and Carter, William E. and Glennie, Craig and Lu, Zhong and Diaz, Juan Carlos Fernandez},
    title = {Evaluation of an airborne {SAR} system for deformation mapping: A case study over the slumgullion landslide},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2017},
    month = jul,
    pages = {1684--1687},
    doi = {10.1109/IGARSS.2017.8127298},
    abstract = {In this study, we present a case study of the Slumgullion landslide conducted in July 2015 to demonstrate the feasibility of deformation mapping with an airborne synthetic aperture radar (SAR) system known as ARTEMIS SlimSAR, which is a compact, modular, and multi-frequency radar system. For this study, the L-band SlimSAR was installed on a Cessna 206 aircraft and data were collected on July 3, 7, and 10 of 2015 and processed using the time-domain backprojection algorithm. Airborne light detection and ranging (LiDAR) campaign, GPS surveys and spaceborne InSAR analysis using COSMO-SkyMed images were also conducted to verify the performance of the airborne SAR system. The airborne InSAR results showed satisfying agreement with the GPS and spaceborne InSAR results. A 3-D deformation map over Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topography.},
    keywords = {SAR Processing, Interferometry, SAR Interferometry, InSAR, Differential SAR Interferometry,DInSAR, Repeat-Pass Interferometry,deformation monitoring, subsidence monitoring, Displacement, Earth, Global Positioning System, Laser radar, Spaceborne radar, Strain, Synthetic aperture radar, Terrain factors, GPS, InSAR, Landslide, LiDAR, SAR},
    owner = {ofrey},
    
    }
    


  2. M. Faisal, M. A. H. Chowdhury, M. A. I. Bhuyan, N. H. M. Bhuyan, and A. Matin. Development of a polarimetric interferometric GB-SAR and perform measurement for a fixed target. In Proc. Computer and Communication Engineering (ECCE) 2017 Int. Conf. Electrical, pages 285-289, February 2017. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, horn antennas, radar antennas, radar interferometry, radar target recognition, synthetic aperture radar, SAR system, antenna positioner, building vehicles, data compression, double ridge guide horn antenna, fixed target, ground vehicles, ground-based synthetic aperture radar system, innovative monitoring technique, perform measurement, polarimetric & interferometric GB-SAR, vector network analyzer, Antenna measurements, Apertures, Frequency-domain analysis, Image reconstruction, Monitoring, Synthetic aperture radar, Time-domain analysis, Global Backprojection (GBP), Ground-Based SAR (GB-SAR), Interferometry, Low loss-high frequency cable, Vector Network Analyzer (VNA).
    @InProceedings{Faisal2017,
    author = {M. Faisal and M. A. H. Chowdhury and M. A. I. Bhuyan and N. H. M. Bhuyan and A. Matin},
    title = {Development of a polarimetric interferometric GB-{SAR} and perform measurement for a fixed target},
    booktitle = {Proc. Computer and Communication Engineering (ECCE) 2017 Int. Conf. Electrical},
    year = {2017},
    month = feb,
    pages = {285--289},
    doi = {10.1109/ECACE.2017.7912919},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,horn antennas, radar antennas, radar interferometry, radar target recognition, synthetic aperture radar, SAR system, antenna positioner, building vehicles, data compression, double ridge guide horn antenna, fixed target, ground vehicles, ground-based synthetic aperture radar system, innovative monitoring technique, perform measurement, polarimetric & interferometric GB-SAR, vector network analyzer, Antenna measurements, Apertures, Frequency-domain analysis, Image reconstruction, Monitoring, Synthetic aperture radar, Time-domain analysis, Global Backprojection (GBP), Ground-Based SAR (GB-SAR), Interferometry, Low loss-high frequency cable, Vector Network Analyzer (VNA)},
    owner = {ofrey},
    
    }
    


  3. Othmar Frey, Charles L. Werner, Rafael Caduff, and Andreas Wiesmann. Inversion of Snow Structure Parameters from Time Series of Tomographic Measurements With SnowScat. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 2472-2475, 2017. 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, SWE, Snow Water Equivalent, Autofocus, Time-Domain Back-Projection, TDBP, Backprojection.
    Abstract: SnowScat is a terrestrial stepped-frequency continuous-wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. Recently, the hardware has been upgraded by adding a tomographic profiling mode. This tomographic approach allows to retrieve high-resolution information about a snowpack via observables, such as radar backscatter, co-polar phase difference, interferometric phase and coherence. Since the tomographic imaging itself is also affected by the refraction occurring at the air-snow interface and within the snowpack the two problems, 1) the production of well-focused and correctly located tomographic profiles, and 2) the retrieval of snow structure parameters are inherently linked. In this contribution, a tomographic inversion scheme to retrieve the refractive index of snow through an autofocus approach is presented. The current autofocus-based retrieval relies on using an aluminium sphere of a test target deployed in the scene. The refractive indices and accompanying snow density measurements obtained at four dates during a cold period in January during the ESA SnowLab 2016/2017 campaign are compared to an empirical model by Matzler and Wiesmann that describes the relation between snow density and the real part of the relative permittivity for dry snow.

    @InProceedings{freyWernerCaduffWiesmannIGARSS2017SnowScatTomoInversionSWE,
    author = {Othmar Frey and Charles L. Werner and Rafael Caduff and Andreas Wiesmann},
    title = {Inversion of Snow Structure Parameters from Time Series of Tomographic Measurements With {SnowScat}},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2017},
    pages = {2472-2475},
    abstract = {SnowScat is a terrestrial stepped-frequency continuous-wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. Recently, the hardware has been upgraded by adding a tomographic profiling mode. This tomographic approach allows to retrieve high-resolution information about a snowpack via observables, such as radar backscatter, co-polar phase difference, interferometric phase and coherence. Since the tomographic imaging itself is also affected by the refraction occurring at the air-snow interface and within the snowpack the two problems, 1) the production of well-focused and correctly located tomographic profiles, and 2) the retrieval of snow structure parameters are inherently linked. In this contribution, a tomographic inversion scheme to retrieve the refractive index of snow through an autofocus approach is presented. The current autofocus-based retrieval relies on using an aluminium sphere of a test target deployed in the scene. The refractive indices and accompanying snow density measurements obtained at four dates during a cold period in January during the ESA SnowLab 2016/2017 campaign are compared to an empirical model by Matzler and Wiesmann that describes the relation between snow density and the real part of the relative permittivity for dry snow.},
    doi = {10.1109/IGARSS.2017.8127494},
    file = {:freyWernerCaduffWiesmannIGARSS2017SnowScatTomoInversionSWE.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, SWE, Snow Water Equivalent, Autofocus, Time-Domain Back-Projection, TDBP, Backprojection},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerCaduffWiesmannIGARSS2017SnowScatTomoInversionSWE.pdf},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8127494},
    
    }
    


  4. Scott Hensley. An analytic expression for the phase noise properties of the Goldstein-Werner power spectral filter. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 3802-3805, July 2017. Keyword(s): Fourier transforms, filters, geophysical signal processing, radar interferometry, remote sensing by radar, spectral analysis, synthetic aperture radar, Fourier transform, Goldstein-Werner power spectral filter, interferogram filtering, maximal noise reduction, phase noise properties, radar interferometric applications, repeat pass radar interferometry, Correlation, Fourier transforms, Noise reduction, Phase noise, Radar, Signal to noise ratio, Transfer functions, Goldstein-Werner filter, filtering, interferogram, phase noise, power spectral filter.
    @InProceedings{hensleyIGARSS2017AnalyticExpressionGoldsteinWernerFilter,
    author = {Scott Hensley},
    title = {An analytic expression for the phase noise properties of the {G}oldstein-{W}erner power spectral filter},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2017},
    pages = {3802--3805},
    month = jul,
    doi = {10.1109/IGARSS.2017.8127828},
    file = {:hensleyIGARSS2017AnalyticExpressionGoldsteinWernerFilter.pdf:PDF},
    keywords = {Fourier transforms, filters, geophysical signal processing, radar interferometry, remote sensing by radar, spectral analysis, synthetic aperture radar, Fourier transform, Goldstein-Werner power spectral filter, interferogram filtering, maximal noise reduction, phase noise properties, radar interferometric applications, repeat pass radar interferometry, Correlation, Fourier transforms, Noise reduction, Phase noise, Radar, Signal to noise ratio, Transfer functions, Goldstein-Werner filter, filtering, interferogram, phase noise, power spectral filter},
    owner = {ofrey},
    
    }
    


  5. Zahra Sadeghi, M. J. Valadan Zoej, A. Hooper, and J. M. Lopez-Sanchez. An Enhanced Polarimetric Persistent Scatterer Interferometry Method to Increase Number and Quality of Selected Pixels. In Proc. FRINGE 2017, Helsinki, Finland, June 2017.
    @Conference{sadeghiValadanZoejHooperLopezSanchezFRINGE2017,
    author = {Sadeghi, Zahra and Valadan Zoej, M. J. and Hooper, A. and Lopez-Sanchez, J. M.},
    title = {An Enhanced Polarimetric Persistent Scatterer Interferometry Method to Increase Number and Quality of Selected Pixels},
    booktitle = {Proc. FRINGE 2017},
    year = {2017},
    address = {Helsinki, Finland},
    month = jun,
    owner = {ofrey},
    
    }
    


  6. M. Schuetz, M. Oesterlein, C. Birkenhauer, and M. Vossiek. A custom lightweight UAV for radar remote sensing: Concept design, properties and possible applications. In 2017 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM), pages 107-110, March 2017. Keyword(s): embedded systems, Global Positioning System, ground penetrating radar, MIMO radar, radar interferometry, remote sensing, synthetic aperture radar, custom lightweight UAV, radar remote sensing, concept design, tailor-made UAV-based sensor platform, radar remote sensing, radar baseband processing, differential GPS system, synthetic apertures, interferometric remote sensing, MIMO radar system, side-looking-airborne-radar, full interferometric SAR processing, radar altimeter measurement, altitude estimators, ultrasonic sensors, barometric sensors, Radar remote sensing, Synthetic aperture radar, Radar antennas, Baseband, Antenna arrays, Clocks, multicopter, UAV, remote sensing, system design, radar system, SAR, interferometry.
    Abstract: In this paper, we introduce a novel, tailor-made UAV-based sensor platform for radar remote sensing. It is controlled by a redundantly implemented, customized flight control and equipped with a comprehensive embedded system for radar baseband processing. Both systems are synchronized with a common, low-phase noise and temperature-stable reference clock, which allows coherent acquisition and continuous recording of sensor data. A commercial differential GPS system is used for positioning. The platform potentially allows interferometric remote sensing with synthetic apertures. In a first case study, it is equipped with a bistatic 24GHz MIMO radar system to create a side-looking-airborne-radar, allowing full interferometric SAR processing. As a proof-of-concept, a radar altimeter measurement is presented, which replaces and outperforms common altitude estimators, such as barometric or ultra sonic sensors.

    @InProceedings{schuetzOsterleinBirkenhauerVossiekConf2017LightweightUAVforRADARremotesensing,
    author = {M. {Schuetz} and M. {Oesterlein} and C. {Birkenhauer} and M. {Vossiek}},
    booktitle = {2017 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)},
    title = {A custom lightweight {UAV} for radar remote sensing: Concept design, properties and possible applications},
    year = {2017},
    month = {March},
    pages = {107-110},
    abstract = {In this paper, we introduce a novel, tailor-made UAV-based sensor platform for radar remote sensing. It is controlled by a redundantly implemented, customized flight control and equipped with a comprehensive embedded system for radar baseband processing. Both systems are synchronized with a common, low-phase noise and temperature-stable reference clock, which allows coherent acquisition and continuous recording of sensor data. A commercial differential GPS system is used for positioning. The platform potentially allows interferometric remote sensing with synthetic apertures. In a first case study, it is equipped with a bistatic 24GHz MIMO radar system to create a side-looking-airborne-radar, allowing full interferometric SAR processing. As a proof-of-concept, a radar altimeter measurement is presented, which replaces and outperforms common altitude estimators, such as barometric or ultra sonic sensors.},
    doi = {10.1109/ICMIM.2017.7918868},
    keywords = {embedded systems;Global Positioning System;ground penetrating radar;MIMO radar;radar interferometry;remote sensing;synthetic aperture radar;custom lightweight UAV;radar remote sensing;concept design;tailor-made UAV-based sensor platform;radar remote sensing;radar baseband processing;differential GPS system;synthetic apertures;interferometric remote sensing;MIMO radar system;side-looking-airborne-radar;full interferometric SAR processing;radar altimeter measurement;altitude estimators;ultrasonic sensors;barometric sensors;Radar remote sensing;Synthetic aperture radar;Radar antennas;Baseband;Antenna arrays;Clocks;multicopter;UAV;remote sensing;system design;radar system;SAR;interferometry},
    
    }
    


  7. M. Adnan Siddique, Irena Hajnsek, and Othmar Frey. A Case Study on the Use of Differential SAR Tomography for Measuring Deformation in Layover Areas in Rugged Alpine Terrain. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 5850-5853, 2017. 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, SAR tomography based 3-D point cloud extraction, high-resolution spaceborne SAR, Cosmo Skymed, interferometric stack, layover scenario case, persistent scatterer interferometry, PSI, point-like scatterer, processing approach, Alpine Remote Sensing, Spaceborne radar, Synthetic aperture radar, Three-dimensional displays, Tomography, 3-D point cloud, SAR interferometry.
    Abstract: Differential SAR tomography is a means to resolve layover of temporally coherent scatterers while simultaneously estimating their elevation and average deformation. In alpine regions, drastic height variations result in frequent layovers which are rejected during typical persistent scatterer interferometric (PSI) analyses. In this paper, we explore the potential of tomographic techniques to improve deformation sampling in an alpine region of interest relative to a PSI-based deformation assessment. The mitigation of the atmospheric phase contributions, as required for both tomography and PSI, is often more involved in alpine regions due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. We assume a linear multivariate dependence of atmospheric phase on the spatial location and height of the scatterers, estimate it using universal/regression kriging and subsequently incorporate it within the tomographic focusing. Experiments are performed on an interferometric stack comprising of 32 Cosmo-SkyMed strimap images acquired in the summers of 2008-2013 over Mattervalley in the Swiss Alps.

    @InProceedings{siddiqueHajnsekFreyIGARSS2017PSITomoAlpine,
    author = {Siddique, M. Adnan and Hajnsek, Irena and Frey, Othmar},
    title = {A Case Study on the Use of Differential {SAR} Tomography for Measuring Deformation in Layover Areas in Rugged Alpine Terrain},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2017},
    pages = {5850-5853},
    abstract = {Differential SAR tomography is a means to resolve layover of temporally coherent scatterers while simultaneously estimating their elevation and average deformation. In alpine regions, drastic height variations result in frequent layovers which are rejected during typical persistent scatterer interferometric (PSI) analyses. In this paper, we explore the potential of tomographic techniques to improve deformation sampling in an alpine region of interest relative to a PSI-based deformation assessment. The mitigation of the atmospheric phase contributions, as required for both tomography and PSI, is often more involved in alpine regions due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. We assume a linear multivariate dependence of atmospheric phase on the spatial location and height of the scatterers, estimate it using universal/regression kriging and subsequently incorporate it within the tomographic focusing. Experiments are performed on an interferometric stack comprising of 32 Cosmo-SkyMed strimap images acquired in the summers of 2008-2013 over Mattervalley in the Swiss Alps.},
    doi = {10.1109/IGARSS.2017.8128339},
    file = {:siddiqueHajnsekFreyIGARSS2017PSITomoAlpine.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; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne SAR, Cosmo Skymed, interferometric stack;layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Alpine 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/siddiqueHajnsekFreyIGARSS2017PSITomoAlpine.pdf},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8128339},
    
    }
    


  8. Hui Wang, Yongjiang Xia, Man Jiang, and Lingzhen Kong. Research on W-band FMCW Rail-SAR system with high resolution. In 2017 18th International Radar Symposium (IRS), pages 1-6, June 2017. Keyword(s): SAR Processing, W-Band, FM radar, millimetre wave radar, radar imaging, radar resolution, synthetic aperture radar, RD imaging algorithm, W-band FMCW rail-SAR system, high resolution imaging, small target imaging, system parameter simulation, Antenna arrays, Azimuth, Imaging, Rails, Signal resolution, Simulation, Synthetic aperture radar.
    Abstract: Combined with short wavelength of the w-band and small volume and low cost advantage of the FMCW SAR, much attention has been paid to the application of W band FMCW SAR with high resolution imaging to close small target imaging. This paper introduces a W-band Rail FMCW SAR used to small target imaging in near-distance. Based on the system parameters simulation and design, the design of the system scheme is also given. In addition, using the modified RD imaging algorithm to get the point target simulation result. The result proves the feasibility and reliability of the system.

    @INPROCEEDINGS{wangXiaJiangKong2017FMCWSARWBAND,
    author={Hui Wang and Yongjiang Xia and Man Jiang and Lingzhen Kong},
    booktitle={2017 18th International Radar Symposium (IRS)},
    title={Research on W-band FMCW Rail-SAR system with high resolution},
    year={2017},
    volume={},
    number={},
    pages={1-6},
    abstract={Combined with short wavelength of the w-band and small volume and low cost advantage of the FMCW SAR, much attention has been paid to the application of W band FMCW SAR with high resolution imaging to close small target imaging. This paper introduces a W-band Rail FMCW SAR used to small target imaging in near-distance. Based on the system parameters simulation and design, the design of the system scheme is also given. In addition, using the modified RD imaging algorithm to get the point target simulation result. The result proves the feasibility and reliability of the system.},
    keywords={SAR Processing, W-Band,FM radar;millimetre wave radar;radar imaging;radar resolution;synthetic aperture radar;RD imaging algorithm;W-band FMCW rail-SAR system;high resolution imaging;small target imaging;system parameter simulation;Antenna arrays;Azimuth;Imaging;Rails;Signal resolution;Simulation;Synthetic aperture radar},
    doi={10.23919/IRS.2017.8008230},
    ISSN={},
    month={June},
    owner = {ofrey},
    
    }
    


Miscellaneous

  1. IEEE Std 686-2017 (Revision of IEEE Std 686-2008), Sep. 2017. Keyword(s): IEEE standards, radar, IEEE standard, radar terminology, IEEE Standards, Radar, Aerospace electronics, Dictionaries, Terminology, IEEE 686(TM), radar, terminology.
    Abstract: The promotion of clarity and consistency in the use of radar terminology is the purpose of the definitions provided in this guide. The consensus of a panel of radar experts are represented in the definitions herein.

    @Standard{IEEEStandard686y2017forRadarDefinitions2017,
    title = {IEEE Std 686-2017 (Revision of IEEE Std 686-2008)},
    organization = {IEEE Standard for Radar Definitions},
    institution = {IEEE},
    month = {Sep.},
    year = {2017},
    abstract = {The promotion of clarity and consistency in the use of radar terminology is the purpose of the definitions provided in this guide. The consensus of a panel of radar experts are represented in the definitions herein.},
    doi = {10.1109/IEEESTD.2017.8048479},
    file = {:IEEEStandard686y2017forRadarDefinitions2017.pdf:PDF},
    journal = {IEEE Std 686-2017 (Revision of IEEE Std 686-2008)},
    keywords = {IEEE standards;radar;IEEE standard;radar terminology;IEEE Standards;Radar;Aerospace electronics;Dictionaries;Terminology;IEEE 686(TM);radar;terminology},
    owner = {ofrey},
    pages = {1-54},
    
    }
    


BACK TO INDEX BACK TO OTHMAR FREY'S HOMEPAGE


Disclaimer:

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 .


This document was translated from BibTEX by bibtex2html