BACK TO INDEX BACK TO OTHMAR FREY'S HOMEPAGE

Publications of year 2019

Books and proceedings

  1. MATLAB. v. 9.6.0.1135713 (R2019a) Update 3. The MathWorks Inc., Natick, Massachusetts, 2019. Note: Function robustfit.
    @Book{MATLAB2019aRobustfit,
    author = {MATLAB},
    publisher = {The MathWorks Inc.},
    title = {v. 9.6.0.1135713 (R2019a) Update 3},
    year = {2019},
    address = {Natick, Massachusetts},
    note = {function robustfit},
    
    }
    


Articles in journal or book chapters

  1. Simone Baffelli, Othmar Frey, and Irena Hajnsek. Polarimetric Analysis of Natural Terrain Observed With a Ku-Band Terrestrial Radar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(12):5268-5288, December 2019. Keyword(s): Terrestrical Radar, Polarimetry, Radar Polarimetry, ku-band, Gamma Portable Radar Interferometer, GPRI-II, Polarimetric Gamma Portable Radar Interferometer, PolGPRI, Entropy, ground based radar, polarimetric radar.
    Abstract: Terrestrial radar interferometers (TRI) are complimentary to spaceborne synthetic aperture radar systems for deformation monitoring in natural terrain: they permit shorter revisit times and greater flexibility in acquisition mode and timing. The additional diversity offered by polarimetric data can also be beneficial for TRI observations because polarized waves are sensitive to the dielectric and geometrical properties of the scatterers. Polarimetric data helps to distinguish different scattering mechanisms in a resolution cell while at the same time estimating terrain displacements. However, the polarimetric scattering signatures of natural surfaces at Ku-Band are not as well characterized as the ones at longer wavelengths, owing to relative rarity of full polarimetric systems operating in Ku-band. This band is often employed in TRI to obtain a fine azimuth resolution with a limited aperture size. This article aims at assessing the potential of polarimetric measurements in Ku-band TRI through an experimental study of polarimetric scattering signatures of natural surfaces using two datasets acquired over a glacier and in an agricultural and urban scene. The main finding of this analysis is that the Cloude-Pottier entropy is high for all land cover types; it is only observed to be less than 0.5 for scatterers with a large radar cross section. Several plausible hypotheses for this observation are formulated and tested, the most likely assumes a combination of depolarizing scattering from natural surfaces and the effect of the large ratio of wavelength to resolution cell size.

    @Article{baffelliFreyHajnsekJSTARS2019PolarimetricAnalysisNaturalTerrainKuBandRadar,
    author = {Simone Baffelli and Othmar Frey and Irena Hajnsek},
    title = {Polarimetric Analysis of Natural Terrain Observed With a {Ku}-Band Terrestrial Radar},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2019},
    volume = {12},
    number = {12},
    pages = {5268-5288},
    month = {Dec},
    issn = {2151-1535},
    abstract = {Terrestrial radar interferometers (TRI) are complimentary to spaceborne synthetic aperture radar systems for deformation monitoring in natural terrain: they permit shorter revisit times and greater flexibility in acquisition mode and timing. The additional diversity offered by polarimetric data can also be beneficial for TRI observations because polarized waves are sensitive to the dielectric and geometrical properties of the scatterers. Polarimetric data helps to distinguish different scattering mechanisms in a resolution cell while at the same time estimating terrain displacements. However, the polarimetric scattering signatures of natural surfaces at Ku-Band are not as well characterized as the ones at longer wavelengths, owing to relative rarity of full polarimetric systems operating in Ku-band. This band is often employed in TRI to obtain a fine azimuth resolution with a limited aperture size. This article aims at assessing the potential of polarimetric measurements in Ku-band TRI through an experimental study of polarimetric scattering signatures of natural surfaces using two datasets acquired over a glacier and in an agricultural and urban scene. The main finding of this analysis is that the Cloude-Pottier entropy is high for all land cover types; it is only observed to be less than 0.5 for scatterers with a large radar cross section. Several plausible hypotheses for this observation are formulated and tested, the most likely assumes a combination of depolarizing scattering from natural surfaces and the effect of the large ratio of wavelength to resolution cell size.},
    doi = {10.1109/JSTARS.2019.2953206},
    file = {:baffelliFreyHajnsekJSTARS2019PolarimetricAnalysisNaturalTerrainKuBandRadar.pdf:PDF},
    keywords = {Terrestrical Radar, Polarimetry, Radar Polarimetry, ku-band, Gamma Portable Radar Interferometer, GPRI-II, Polarimetric Gamma Portable Radar Interferometer, PolGPRI, Entropy;ground based radar;polarimetric radar},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/baffelliFreyHajnsekJSTARS2019PolarimetricAnalysisNaturalTerrainKuBandRadar.pdf},
    
    }
    


  2. Ibrahim El Moussawi, Dinh Ho Tong Minh, Nicolas Baghdadi, Chadi Abdallah, Jalal Jomaah, Olivier Strauss, Marco Lavalle, and Yen-Nhi Ngo. Monitoring Tropical Forest Structure Using SAR Tomography at L- and P-Band. Remote Sensing, 11(16), 2019.
    Abstract: Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band’s performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities.

    @Article{elMoussawiHoTongHoBaghdadiAbdallahJomaahStraussLavalleNgoREMOTESENSING2019SARTomoLbandPband,
    author = {El Moussawi, Ibrahim and Ho Tong Minh, Dinh and Baghdadi, Nicolas and Abdallah, Chadi and Jomaah, Jalal and Strauss, Olivier and Lavalle, Marco and Ngo, Yen-Nhi},
    journal = {Remote Sensing},
    title = {Monitoring Tropical Forest Structure Using {SAR} Tomography at {L-} and {P-}Band},
    year = {2019},
    issn = {2072-4292},
    number = {16},
    volume = {11},
    abstract = {Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band’s performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities.},
    article-number = {1934},
    doi = {10.3390/rs11161934},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/11/16/1934},
    
    }
    


  3. D. Feng, D. An, X. Huang, and Y. Li. A Phase Calibration Method Based on Phase Gradient Autofocus for Airborne Holographic SAR Imaging. IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2019. Keyword(s): Calibration, Imaging, Synthetic aperture radar, Electronics packaging, Image reconstruction, Radar polarimetry, Azimuth, Holographic synthetic aperture radar (HoloSAR) tomography, phase calibration, phase gradient autofocus (PGA), three-dimensional (3-D) imaging..
    Abstract: Holographic synthetic aperture radar tomography can realize full 3-D reconstructions of objects over 360� with very high resolution, and thus becomes an interesting 3-D imaging technique. However, due to the uncompensated platform motion errors, phase errors among different tracks usually exist in this imaging mode, which will hinder the 3-D image focusing. In this letter, a phase calibration method based on phase gradient autofocus is proposed to mitigate the influence of these phase errors. It exploits the space-invariant characteristic of the phase errors in a limited scene and uses an efficient and robust multibaseline autofocus to calibrate the phase errors among the multiple circular tracks. Experimental results with the GOTCHA real data are carried out to demonstrate the validity and feasibility of the proposed method.

    @Article{FengAnHuangLiGRSL2019SARTomoPGAPhaseCalibration,
    author = {D. {Feng} and D. {An} and X. {Huang} and Y. {Li}},
    title = {A Phase Calibration Method Based on Phase Gradient Autofocus for Airborne Holographic SAR Imaging},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2019},
    pages = {1-5},
    issn = {1545-598X},
    abstract = {Holographic synthetic aperture radar tomography can realize full 3-D reconstructions of objects over 360� with very high resolution, and thus becomes an interesting 3-D imaging technique. However, due to the uncompensated platform motion errors, phase errors among different tracks usually exist in this imaging mode, which will hinder the 3-D image focusing. In this letter, a phase calibration method based on phase gradient autofocus is proposed to mitigate the influence of these phase errors. It exploits the space-invariant characteristic of the phase errors in a limited scene and uses an efficient and robust multibaseline autofocus to calibrate the phase errors among the multiple circular tracks. Experimental results with the GOTCHA real data are carried out to demonstrate the validity and feasibility of the proposed method.},
    doi = {10.1109/LGRS.2019.2911932},
    keywords = {Calibration;Imaging;Synthetic aperture radar;Electronics packaging;Image reconstruction;Radar polarimetry;Azimuth;Holographic synthetic aperture radar (HoloSAR) tomography;phase calibration;phase gradient autofocus (PGA);three-dimensional (3-D) imaging.},
    owner = {ofrey},
    
    }
    


  4. Weike Feng, Jean-Michel Friedt, Giovanni Nico, Suyun Wang, Gilles Martin, and Motoyuki Sato. Passive Bistatic Ground-Based Synthetic Aperture Radar: Concept, System, and Experiment Results. Remote Sensing, 11(15), 2019.
    Abstract: A passive bistatic ground-based synthetic aperture radar (PB-GB-SAR) system without a dedicated transmitter has been developed by using commercial-off-the-shelf (COTS) hardware for local-area high-resolution imaging and displacement measurement purposes. Different from the frequency-modulated or frequency-stepped continuous wave signal commonly used by GB-SAR, the continuous digital TV signal broadcast by a geostationary satellite has been adopted by PB-GB-SAR. In order to increase the coherence between the reference and surveillance channels, frequency and phase synchronization of multiple low noise blocks (LNBs) has been conducted. Then, the back-projection algorithm (BPA) and the range migration algorithm (RMA) have been modified for PB-GB-SAR to get the focused SAR image. Field experiments have been carried out to validate the designed PB-GB-SAR system and the proposed methods. It has been found that different targets within 100 m (like the fence, light pole, tree, and car) can be imaged by the PB-GB-SAR system. With a metallic plate moved on a positioner, it has been observed that the displacement of the target can be estimated by PB-GB-SAR with submillimeter accuracy.

    @Article{fengFriedtNicoWangMartinSatoREMOTESENSING2019PassiveBistaticGroundbasedSAR,
    author = {Feng, Weike and Friedt, Jean-Michel and Nico, Giovanni and Wang, Suyun and Martin, Gilles and Sato, Motoyuki},
    journal = {Remote Sensing},
    title = {Passive Bistatic Ground-Based Synthetic Aperture Radar: Concept, System, and Experiment Results},
    year = {2019},
    issn = {2072-4292},
    number = {15},
    volume = {11},
    abstract = {A passive bistatic ground-based synthetic aperture radar (PB-GB-SAR) system without a dedicated transmitter has been developed by using commercial-off-the-shelf (COTS) hardware for local-area high-resolution imaging and displacement measurement purposes. Different from the frequency-modulated or frequency-stepped continuous wave signal commonly used by GB-SAR, the continuous digital TV signal broadcast by a geostationary satellite has been adopted by PB-GB-SAR. In order to increase the coherence between the reference and surveillance channels, frequency and phase synchronization of multiple low noise blocks (LNBs) has been conducted. Then, the back-projection algorithm (BPA) and the range migration algorithm (RMA) have been modified for PB-GB-SAR to get the focused SAR image. Field experiments have been carried out to validate the designed PB-GB-SAR system and the proposed methods. It has been found that different targets within 100 m (like the fence, light pole, tree, and car) can be imaged by the PB-GB-SAR system. With a metallic plate moved on a positioner, it has been observed that the displacement of the target can be estimated by PB-GB-SAR with submillimeter accuracy.},
    article-number = {1753},
    doi = {10.3390/rs11151753},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/11/15/1753},
    
    }
    


  5. Xikai Fu, Bingnan Wang, Maosheng Xiang, Shuai Jiang, and Xiaofan Sun. Residual RCM Correction for LFM-CW Mini-SAR System Based on Fast-Time Split-Band Signal Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 57(7):4375-4387, July 2019.
    @Article{fuWangXiangJiangSunTGRS2019ResidualMotionCorrectionForLFMCWMiniSAR,
    author = {Xikai Fu and Bingnan Wang and Maosheng Xiang and Shuai Jiang and Xiaofan Sun},
    journal = {{IEEE} Transactions on Geoscience and Remote Sensing},
    title = {Residual {RCM} Correction for {LFM}-{CW} Mini-{SAR} System Based on Fast-Time Split-Band Signal Interferometry},
    year = {2019},
    month = {jul},
    number = {7},
    pages = {4375--4387},
    volume = {57},
    doi = {10.1109/TGRS.2019.2890978},
    owner = {ofrey},
    publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
    
    }
    


  6. Nan Ge and Xiao Xiang Zhu. Bistatic-Like Differential SAR Tomography. IEEE Trans. Geosci. Remote Sens., pp 1-11, 2019. Keyword(s): Synthetic aperture radar, Strain, Satellites, Satellite broadcasting, Spaceborne radar, Decorrelation, Tomography, Synthetic aperture radar (SAR), SAR tomography, Tandem-L, TerraSAR-X add-on for digital elevation measurements (TanDEM-X)..
    Abstract: Motivated by prospective synthetic aperture radar (SAR) satellite missions, this paper addresses the problem of differential SAR tomography (D-TomoSAR) in urban areas using spaceborne bistatic or pursuit monostatic acquisitions. A bistatic or pursuit monostatic interferogram is not subject to significant temporal decorrelation or atmospheric phase screen and, therefore, ideal for elevation reconstruction. We propose a framework that incorporates this reconstructed elevation as deterministic prior to deformation estimation, which uses conventional repeat-pass interferograms generated from bistatic or pursuit monostatic pairs. By means of theoretical and empirical analyses, we show that this framework is, in the pursuit monostatic case, both statistically and computationally more efficient than the standard D-TomoSAR. In the bistatic case, its theoretical bound is no worse by a factor of 2. We also show that reasonable results can be obtained by using merely six TerraSAR-X add-on for digital elevation measurements (TanDEM-X) pursuit monostatic pairs, if additional spatial prior is introduced. The proposed framework can be easily extended for multistatic configurations or external sources of scatterer's elevation.

    @Article{geZhuTGRS2019BistaticLikeDiffTOMOSAR,
    author = {Ge, Nan and Zhu, Xiao Xiang},
    title = {Bistatic-Like Differential {SAR} Tomography},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2019},
    pages = {1-11},
    issn = {0196-2892},
    abstract = {Motivated by prospective synthetic aperture radar (SAR) satellite missions, this paper addresses the problem of differential SAR tomography (D-TomoSAR) in urban areas using spaceborne bistatic or pursuit monostatic acquisitions. A bistatic or pursuit monostatic interferogram is not subject to significant temporal decorrelation or atmospheric phase screen and, therefore, ideal for elevation reconstruction. We propose a framework that incorporates this reconstructed elevation as deterministic prior to deformation estimation, which uses conventional repeat-pass interferograms generated from bistatic or pursuit monostatic pairs. By means of theoretical and empirical analyses, we show that this framework is, in the pursuit monostatic case, both statistically and computationally more efficient than the standard D-TomoSAR. In the bistatic case, its theoretical bound is no worse by a factor of 2. We also show that reasonable results can be obtained by using merely six TerraSAR-X add-on for digital elevation measurements (TanDEM-X) pursuit monostatic pairs, if additional spatial prior is introduced. The proposed framework can be easily extended for multistatic configurations or external sources of scatterer's elevation.},
    doi = {10.1109/TGRS.2019.2902814},
    file = {:geZhuTGRS2019BistaticLikeDiffTOMOSAR.pdf:PDF},
    keywords = {Synthetic aperture radar;Strain;Satellites;Satellite broadcasting;Spaceborne radar;Decorrelation;Tomography;Synthetic aperture radar (SAR);SAR tomography;Tandem-L;TerraSAR-X add-on for digital elevation measurements (TanDEM-X).},
    owner = {ofrey},
    
    }
    


  7. Changzhan Gu, Jian Wang, and Jaime Lien. Motion Sensing Using Radar: Gesture Interaction and Beyond. IEEE Microwave Magazine, 20(8):44-57, August 2019. Keyword(s): Android (operating system), artificial intelligence, gesture recognition, iOS (operating system), mobile computing, smart phones, Android smartphones, motion sensing, iOS, mobile computing platform, gesture interaction, artificial intelligence, Radar detection, Gesture recognition, Artificial intelligence, Mobile computing, Sensors, Motion detection.
    Abstract: Since the debut of iOS and Android smartphones 10 years ago, the world has seen a mobile era wherein our phones have become a mobile computing platform deeply integrated into our lives [1]-[4]. Due to the advancement of computing, it is believed that the world is shifting to a new era where artificial intelligence (AI) is unlocking capabilities that were previously unthinkable [5]-[13]. Because computing is becoming more universally available, interaction with computing devices needs to be much more natural, intuitive, and, above all, intelligent [14].

    @Article{guWangLienIEEEMWMagazine2019MotionSensingRadarGestureInteractionGOOGLEProjectSoli,
    author = {Changzhan Gu and Jian Wang and Jaime Lien},
    journal = {IEEE Microwave Magazine},
    title = {Motion Sensing Using Radar: Gesture Interaction and Beyond},
    year = {2019},
    issn = {1557-9581},
    month = {Aug},
    number = {8},
    pages = {44-57},
    volume = {20},
    abstract = {Since the debut of iOS and Android smartphones 10 years ago, the world has seen a mobile era wherein our phones have become a mobile computing platform deeply integrated into our lives [1]-[4]. Due to the advancement of computing, it is believed that the world is shifting to a new era where artificial intelligence (AI) is unlocking capabilities that were previously unthinkable [5]-[13]. Because computing is becoming more universally available, interaction with computing devices needs to be much more natural, intuitive, and, above all, intelligent [14].},
    doi = {10.1109/MMM.2019.2915490},
    keywords = {Android (operating system);artificial intelligence;gesture recognition;iOS (operating system);mobile computing;smart phones;Android smartphones;motion sensing;iOS;mobile computing platform;gesture interaction;artificial intelligence;Radar detection;Gesture recognition;Artificial intelligence;Mobile computing;Sensors;Motion detection},
    
    }
    


  8. C. Hu, B. Zhang, X. Dong, and Y. Li. Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite. IEEE Transactions on Geoscience and Remote Sensing, pp 1-17, 2019. Keyword(s): Orbits, Synthetic aperture radar, Tomography, Satellites, Perturbation methods, Radar imaging, 3-D imaging, Beidou inclined geosynchronous orbit (IGSO), geosynchronous synthetic aperture radar (GEO SAR), tomography..
    Abstract: Synthetic aperture radar (SAR) tomography (TomoSAR) techniques exploit multipass acquisitions of the same scene with slightly different view angles, and allow generating fully 3-D images, providing an estimation of scatterers' distribution along range, azimuth, and elevation directions. This paper extends TomoSAR to geosynchronous SAR (GEO TomoSAR). First, the potential and performance of GEO TomoSAR were analyzed from the perspective of orbital perturbation and the resulting large spatial baseline. Then, the rotation-induced decorrelation problems induced by the along-track baseline component were analyzed. In addition, the optimized acquisition geometry and tomographic processing flow were given, and the computer simulation verification was also completed. Finally, the equivalent validation experiment based on Beidou inclined geosynchronous orbit (IGSO) navigation satellite was carried out to demonstrate the feasibility and effectiveness of GEO TomoSAR. The experimental system employs the Beidou IGSO satellite as illuminator of opportunity and a ground system collecting and processing reflected echoes. This is the first time to employ the data from repeat-track Beidou IGSO satellites for tomographic processing. The 3-D imaging of the urban area using this experimental system was presented and then verified using LiDAR cloud data as reference. The results show that GEO TomoSAR can form the baseline of the order of hundreds of kilometers in elevation, which has the ability to achieve a resolution of 5 m in elevation.

    @Article{huZhangDongLiTGRS2019GeosynchronousSARTomography,
    author = {Hu, C. and Zhang, B. and Dong, X. and Li,Y.},
    title = {Geosynchronous {SAR} Tomography: Theory and First Experimental Verification Using {Beidou} {IGSO} Satellite},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    pages = {1-17},
    issn = {0196-2892},
    abstract = {Synthetic aperture radar (SAR) tomography (TomoSAR) techniques exploit multipass acquisitions of the same scene with slightly different view angles, and allow generating fully 3-D images, providing an estimation of scatterers' distribution along range, azimuth, and elevation directions. This paper extends TomoSAR to geosynchronous SAR (GEO TomoSAR). First, the potential and performance of GEO TomoSAR were analyzed from the perspective of orbital perturbation and the resulting large spatial baseline. Then, the rotation-induced decorrelation problems induced by the along-track baseline component were analyzed. In addition, the optimized acquisition geometry and tomographic processing flow were given, and the computer simulation verification was also completed. Finally, the equivalent validation experiment based on Beidou inclined geosynchronous orbit (IGSO) navigation satellite was carried out to demonstrate the feasibility and effectiveness of GEO TomoSAR. The experimental system employs the Beidou IGSO satellite as illuminator of opportunity and a ground system collecting and processing reflected echoes. This is the first time to employ the data from repeat-track Beidou IGSO satellites for tomographic processing. The 3-D imaging of the urban area using this experimental system was presented and then verified using LiDAR cloud data as reference. The results show that GEO TomoSAR can form the baseline of the order of hundreds of kilometers in elevation, which has the ability to achieve a resolution of 5 m in elevation.},
    doi = {10.1109/TGRS.2019.2907369},
    file = {:huZhangDongLiTGRS2019GeosynchronousSARTomography.pdf:PDF},
    keywords = {Orbits;Synthetic aperture radar;Tomography;Satellites;Perturbation methods;Radar imaging;3-D imaging;Beidou inclined geosynchronous orbit (IGSO);geosynchronous synthetic aperture radar (GEO SAR);tomography.},
    owner = {ofrey},
    
    }
    


  9. Unmesh Khati, Marco Lavalle, and Gulab Singh. Spaceborne tomography of multi-species Indian tropical forests. Remote Sensing of Environment, 229:193-212, 2019. Keyword(s): SAR Processing, SAR Tomography, TomoSAR, Tomography, TanDEM-X, TerraSAR-X, Tropical, Forest, India, Spaceborne SAR, X-band.
    Abstract: Synthetic Aperture Radar (SAR) backscatter is the coherent combination of the scattering from multiple individual scatterers within the radar resolution cell, which results into a 2-D radar image. Tomographic SAR (TomoSAR) takes advantage of multiple SAR acquisitions to provide 3-D vertical structure of the imaged target. Over forests, parameters such as canopy structure, canopy density, leaf area and phenology contribute to different SAR scattering mechanisms along the vertical dimension of the trees. Tomography has been demonstrated in various earlier works for forest bio-physical parameter estimation using airborne data. In this research work, multi-polarimetric space-borne TanDEM-X tomograms are examined for the first time over a multi-species Indian tropical forest. Multiple TanDEM-X acquisitions are focused using Capon beamforming at five polarimetric channels HH, HV, VV, HH-VV, HH+VV. Four distinct forest species compartments are selected representing different canopy structure and density. The tomograms obtained in different polarizations for these species are analyzed in detail to understand the scattering patterns across different forest species. Field surveys carried out in several forest locations provide in situ observations of forest height and vertical structure. It was observed that canopy gaps and leaf density play a crucial role for X-band SAR signal penetration through ground. For dense canopy species the backscatter contributions are spread through the canopy, while in case of sparse canopy species, the ground scattering is dominant. Vertical profiles obtained at surveyed plot locations are plotted in all polarizations, and provide a good agreement with field observations. Further, the obtained TomoSAR backscatter layers have a good correlation with field measured above-ground biomass (AGB). The AGB is modeled from TomoSAR with the HH-pol TomoSAR backscatter layer at 27m canopy height leading to an AGB estimation with correlation r=0.76 and RMSE of 50.4t/ha.

    @Article{khatiLavalleSinghRSE2019SpaceborneSARTomographyIndianForest,
    author = {Unmesh Khati and Marco Lavalle and Gulab Singh},
    journal = {Remote Sensing of Environment},
    title = {Spaceborne tomography of multi-species {Indian} tropical forests},
    year = {2019},
    issn = {0034-4257},
    pages = {193-212},
    volume = {229},
    abstract = {Synthetic Aperture Radar (SAR) backscatter is the coherent combination of the scattering from multiple individual scatterers within the radar resolution cell, which results into a 2-D radar image. Tomographic SAR (TomoSAR) takes advantage of multiple SAR acquisitions to provide 3-D vertical structure of the imaged target. Over forests, parameters such as canopy structure, canopy density, leaf area and phenology contribute to different SAR scattering mechanisms along the vertical dimension of the trees. Tomography has been demonstrated in various earlier works for forest bio-physical parameter estimation using airborne data. In this research work, multi-polarimetric space-borne TanDEM-X tomograms are examined for the first time over a multi-species Indian tropical forest. Multiple TanDEM-X acquisitions are focused using Capon beamforming at five polarimetric channels HH, HV, VV, HH-VV, HH+VV. Four distinct forest species compartments are selected representing different canopy structure and density. The tomograms obtained in different polarizations for these species are analyzed in detail to understand the scattering patterns across different forest species. Field surveys carried out in several forest locations provide in situ observations of forest height and vertical structure. It was observed that canopy gaps and leaf density play a crucial role for X-band SAR signal penetration through ground. For dense canopy species the backscatter contributions are spread through the canopy, while in case of sparse canopy species, the ground scattering is dominant. Vertical profiles obtained at surveyed plot locations are plotted in all polarizations, and provide a good agreement with field observations. Further, the obtained TomoSAR backscatter layers have a good correlation with field measured above-ground biomass (AGB). The AGB is modeled from TomoSAR with the HH-pol TomoSAR backscatter layer at 27m canopy height leading to an AGB estimation with correlation r=0.76 and RMSE of 50.4t/ha.},
    doi = {https://doi.org/10.1016/j.rse.2019.04.017},
    file = {:khatiLavalleSinghRSE2019SpaceborneSARTomographyIndianForest.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, TomoSAR, Tomography, TanDEM-X, TerraSAR-X, Tropical, Forest, India, Spaceborne SAR, X-band},
    url = {http://www.sciencedirect.com/science/article/pii/S0034425719301622},
    
    }
    


  10. Martina Lagasio, Antonio Parodi, Luca Pulvirenti, Agostino N. Meroni, Giorgio Boni, Nazzareno Pierdicca, Frank S. Marzano, Lorenzo Luini, Giovanna Venuti, Eugenio Realini, Andrea Gatti, Giulio Tagliaferro, Stefano Barindelli, Andrea Monti Guarnieri, Klodiana Goga, Olivier Terzo, Alessio Rucci, Emanuele Passera, Dieter Kranzlmueller, and Bjorn Rommen. A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast. Remote Sensing, 11(20), 2019. Keyword(s): SAR Processing, Weather, Forecasting, Precipitation Forecasting, SAR, GNSS, Zenith Path Delay, Troposphere.
    Abstract: The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied--a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.

    @Article{lagasioEtAlInclPierdiccaTagliaferroMontiGuarnieriRommenREMOTESENSING2019SynergisticUseOfHighResNumericalWeatherPredictionAndEarthObservationToImprovePrecipitationForecast,
    author = {Lagasio, Martina and Parodi, Antonio and Pulvirenti, Luca and Meroni, Agostino N. and Boni, Giorgio and Pierdicca, Nazzareno and Marzano, Frank S. and Luini, Lorenzo and Venuti, Giovanna and Realini, Eugenio and Gatti, Andrea and Tagliaferro, Giulio and Barindelli, Stefano and Monti Guarnieri, Andrea and Goga, Klodiana and Terzo, Olivier and Rucci, Alessio and Passera, Emanuele and Kranzlmueller, Dieter and Rommen, Bjorn},
    journal = {Remote Sensing},
    title = {A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast},
    year = {2019},
    issn = {2072-4292},
    number = {20},
    volume = {11},
    abstract = {The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied--a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.},
    article-number = {2387},
    doi = {10.3390/rs11202387},
    file = {:lagasioEtAlInclPierdiccaTagliaferroMontiGuarnieriRommenREMOTESENSING2019SynergisticUseOfHighResNumericalWeatherPredictionAndEarthObservationToImprovePrecipitationForecast.pdf:PDF},
    keywords = {SAR Processing, Weather, Forecasting, Precipitation Forecasting, SAR, GNSS, Zenith Path Delay, Troposphere},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/11/20/2387},
    
    }
    


  11. Mauro Mariotti d'Alessandro and Stefano Tebaldini. Cross Sensor Simulation of Tomographic SAR Stacks. Remote Sensing, 11(18), 2019. Keyword(s): SAR Processing, tomography, SAR tomography, Simulation, Wavenumbers, orbits, biomass, synthetic aperture radar, P-band.
    Abstract: This paper presents an algorithm for simulating tomographic synthetic aperture radar (SAR) data based on another stack actually gathered by a real acquisition system. Through the procedure here proposed, the simulated system can be evaluated according to its capability to image complex natural media rather than reference point targets. This feature is particularly important whenever the biophysical properties of the target of interest must be preserved and cannot be easily modeled. The system to be simulated may be different from the original one concerning resolution, off-nadir angles, bandwidth and central frequency. The algorithm here proposed handles these differences by properly taking into account the wavenumbers of the target illuminated by the real survey and requested by the simulated one. The complex images constituting the synthetic stack are associated with the effective vertical interferometric wavenumber peculiar of the geometry to be simulated, regardless of the original data. Furthermore, the three-dimensional resolution cell of the simulated tomographic system is consistent with the simulated geometry concerning size and spatial orientation. These two latter features cannot be guaranteed by simply filtering the original stack. The simulator here proposed has been used to simulate the tomographic stack expected from the forthcoming European Space Agency (ESA) BIOMASS mission. The relationship between baseline distribution and 3D focusing capability was explored; special attention has been paid to the robustness of tomographic power at being a good proxy for the above ground biomass in tropical regions.

    @Article{mariottiDAlessandroTebaldiniRemoteSensing2019CrossSensorTomoStackSimulation,
    author = {Mariotti d'Alessandro, Mauro and Tebaldini, Stefano},
    title = {Cross Sensor Simulation of Tomographic {SAR} Stacks},
    journal = {Remote Sensing},
    year = {2019},
    volume = {11},
    number = {18},
    issn = {2072-4292},
    abstract = {This paper presents an algorithm for simulating tomographic synthetic aperture radar (SAR) data based on another stack actually gathered by a real acquisition system. Through the procedure here proposed, the simulated system can be evaluated according to its capability to image complex natural media rather than reference point targets. This feature is particularly important whenever the biophysical properties of the target of interest must be preserved and cannot be easily modeled. The system to be simulated may be different from the original one concerning resolution, off-nadir angles, bandwidth and central frequency. The algorithm here proposed handles these differences by properly taking into account the wavenumbers of the target illuminated by the real survey and requested by the simulated one. The complex images constituting the synthetic stack are associated with the effective vertical interferometric wavenumber peculiar of the geometry to be simulated, regardless of the original data. Furthermore, the three-dimensional resolution cell of the simulated tomographic system is consistent with the simulated geometry concerning size and spatial orientation. These two latter features cannot be guaranteed by simply filtering the original stack. The simulator here proposed has been used to simulate the tomographic stack expected from the forthcoming European Space Agency (ESA) BIOMASS mission. The relationship between baseline distribution and 3D focusing capability was explored; special attention has been paid to the robustness of tomographic power at being a good proxy for the above ground biomass in tropical regions.},
    article-number = {2099},
    doi = {10.3390/rs11182099},
    file = {:mariottiDAlessandroTebaldiniRemoteSensing2019CrossSensorTomoStackSimulation.pdf:PDF},
    keywords = {SAR Processing, tomography, SAR tomography, Simulation, Wavenumbers, orbits, biomass, synthetic aperture radar , P-band},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/11/18/2099},
    
    }
    


  12. J. Matar, M. Rodriguez-Cassola, G. Krieger, P. Lopez-Dekker, and A. Moreira. MEO SAR: System Concepts and Analysis. IEEE Transactions on Geoscience and Remote Sensing, pp 1-12, 2019. Keyword(s): Orbits, Sensitivity, Synthetic aperture radar, Antennas, Spatial resolution, Low earth orbit satellites, Coverage, medium-Earth-orbit (MEO) synthetic aperture radar (SAR), orbits, SAR, space radiation, system performance..
    Abstract: Existing microwave remote sensing instruments used for Earth observation face a clear tradeoff between spatial resolution and revisit times at global scales. The typical imaging capabilities of current systems range from daily observations at kilometer-scale resolutions provided by scatterometers to meter-scale resolutions at lower temporal rates (more than ten days) typical of synthetic aperture radars (SARs). A natural way to fill the gap between these two extremes is to use medium-Earth-orbit SAR (MEO-SAR) systems. MEO satellites are deployed at altitudes above the region of low Earth orbits (LEOs), ending at around 2000 km and below the geosynchronous orbits (GEOs) near 35,786 km. MEO SAR shows a clear potential to provide advantages in terms of spatial coverage, downlink visibility, and global temporal revisit times, e.g., providing moderate resolution images (some tens of meters) at daily rates. This article discusses the design tradeoffs of MEO SAR, including sensitivity and orbit selection. The use of these higher orbits opens the door to global coverage in one- to two-day revisit or continental/oceanic coverage with multidaily observations, making MEO SAR very attractive for future scientific missions with specific interferometric and polarimetric capabilities.

    @Article{matarRodriguezCassolaKriegerLopezMoreiraTGRSMEOSARsystemConcepts,
    author = {J. {Matar} and M. {Rodriguez-Cassola} and G. {Krieger} and P. {Lopez-Dekker} and A. {Moreira}},
    title = {MEO SAR: System Concepts and Analysis},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    pages = {1-12},
    issn = {1558-0644},
    abstract = {Existing microwave remote sensing instruments used for Earth observation face a clear tradeoff between spatial resolution and revisit times at global scales. The typical imaging capabilities of current systems range from daily observations at kilometer-scale resolutions provided by scatterometers to meter-scale resolutions at lower temporal rates (more than ten days) typical of synthetic aperture radars (SARs). A natural way to fill the gap between these two extremes is to use medium-Earth-orbit SAR (MEO-SAR) systems. MEO satellites are deployed at altitudes above the region of low Earth orbits (LEOs), ending at around 2000 km and below the geosynchronous orbits (GEOs) near 35,786 km. MEO SAR shows a clear potential to provide advantages in terms of spatial coverage, downlink visibility, and global temporal revisit times, e.g., providing moderate resolution images (some tens of meters) at daily rates. This article discusses the design tradeoffs of MEO SAR, including sensitivity and orbit selection. The use of these higher orbits opens the door to global coverage in one- to two-day revisit or continental/oceanic coverage with multidaily observations, making MEO SAR very attractive for future scientific missions with specific interferometric and polarimetric capabilities.},
    doi = {10.1109/TGRS.2019.2945875},
    keywords = {Orbits;Sensitivity;Synthetic aperture radar;Antennas;Spatial resolution;Low earth orbit satellites;Coverage;medium-Earth-orbit (MEO) synthetic aperture radar (SAR);orbits;SAR;space radiation;system performance.},
    owner = {ofrey},
    
    }
    


  13. Albert R. Monteith, Lars M. H. Ulander, and Stefano Tebaldini. Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media. Remote Sensing, 11(24), 2019. Keyword(s): SAR Tomography, BorealScat.
    Abstract: Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions.

    @Article{monteithUlanderTebaldiniRemoteSensing2019CalibrationOfGBArrayRadarForTomographicImaging,
    author = {Monteith, Albert R. and Ulander, Lars M. H. and Tebaldini, Stefano},
    journal = {Remote Sensing},
    title = {Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media},
    year = {2019},
    issn = {2072-4292},
    number = {24},
    volume = {11},
    abstract = {Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions.},
    article-number = {2924},
    doi = {10.3390/rs11242924},
    file = {:monteithUlanderTebaldiniRemoteSensing2019CalibrationOfGBArrayRadarForTomographicImaging.pdf:PDF},
    keywords = {SAR Tomography, BorealScat},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/11/24/2924},
    
    }
    


  14. Elias Mndez Domnguez, Christophe Magnard, Erich Meier, David Small, Michael E. Schaepman, and Daniel Henke. A Back-Projection Tomographic Framework for VHR SAR Image Change Detection. IEEE Transactions on Geoscience and Remote Sensing, 57(7):4470-4484, July 2019. Keyword(s): Synthetic aperture radar, Tomography, Backscatter, Apertures, Laser radar, Image resolution, Detectors, Image processing, Markov processes, synthetic aperture radar (SAR), tomography, urban areas.
    Abstract: Information on 3-D structure expands the scope of change detection applications, for example, in urban studies, human activity, and forest monitoring. Current change detection methods do not fully consider the specifics of SAR data or the properties of the corresponding image focusing techniques. We propose a three-stage method complementing the properties of 2-D and 3-D very high-resolution (VHR) synthetic aperture radar imagery to improve the performance of 2-D only approaches. The method takes advantage of back-projection tomography to ease translation of the 2-D location of the targets into their corresponding 3-D location and vice versa. Detection of changes caused by objects with a small vertical extent is based on the corresponding backscatter difference, while changes caused by objects with a large vertical extent are detected with both backscatter and height difference information combined in a conditional random field. Using multitemporal images, the kappa coefficient improved by a factor of two in comparison with traditional schemes.

    @Article{dominguezMagnardMeierSmallSchaepmanHenke2019TDBPTomographyforVHRSARChangeDetection,
    author = {M{\'e}ndez Dom{\'i}nguez, Elias and Magnard, Christophe and Meier, Erich and Small, David and Schaepman, Michael E. and Henke, Daniel},
    title = {A Back-Projection Tomographic Framework for VHR SAR Image Change Detection},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    volume = {57},
    number = {7},
    pages = {4470-4484},
    month = jul,
    issn = {0196-2892},
    abstract = {Information on 3-D structure expands the scope of change detection applications, for example, in urban studies, human activity, and forest monitoring. Current change detection methods do not fully consider the specifics of SAR data or the properties of the corresponding image focusing techniques. We propose a three-stage method complementing the properties of 2-D and 3-D very high-resolution (VHR) synthetic aperture radar imagery to improve the performance of 2-D only approaches. The method takes advantage of back-projection tomography to ease translation of the 2-D location of the targets into their corresponding 3-D location and vice versa. Detection of changes caused by objects with a small vertical extent is based on the corresponding backscatter difference, while changes caused by objects with a large vertical extent are detected with both backscatter and height difference information combined in a conditional random field. Using multitemporal images, the kappa coefficient improved by a factor of two in comparison with traditional schemes.},
    doi = {10.1109/TGRS.2019.2891308},
    file = {:dominguezMagnardMeierSmallSchaepmanHenke2019TDBPTomographyforVHRSARChangeDetection.pdf:PDF},
    keywords = {Synthetic aperture radar;Tomography;Backscatter;Apertures;Laser radar;Image resolution;Detectors;Image processing;Markov processes;synthetic aperture radar (SAR);tomography;urban areas},
    owner = {ofrey},
    
    }
    


  15. Matteo Pardini, John Armston, Wenlu Qi, Seung Kuk Lee, Marivi Tello, Victor Cazcarra Bes, Changhyun Choi, Konstantinos P. Papathanassiou, Ralph O. Dubayah, and Lola E. Fatoyinbo. Early Lessons on Combining Lidar and Multi-baseline SAR Measurements for Forest Structure Characterization. Surveys in Geophysics, 40(4):803-837, July 2019. Keyword(s): SAR Processing, Forest, Biomass, LiDAR, SAR Tomography, Multibaseline SAR.
    Abstract: The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements provided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established framework for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns.

    @Article{pardiniEtAlSURVEYGeophysics2019CombiningLiDARandTomoSARForestStructure,
    author = {Matteo Pardini and John Armston and Wenlu Qi and Seung Kuk Lee and Marivi Tello and Victor Cazcarra Bes and Changhyun Choi and Konstantinos P. Papathanassiou and Ralph O. Dubayah and Lola E. Fatoyinbo},
    journal = {Surveys in Geophysics},
    title = {Early Lessons on Combining Lidar and Multi-baseline {SAR} Measurements for Forest Structure Characterization},
    year = {2019},
    month = {jul},
    number = {4},
    pages = {803--837},
    volume = {40},
    abstract = {The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements provided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established framework for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns.},
    doi = {10.1007/s10712-019-09553-9},
    file = {:pardiniEtAlSURVEYGeophysics2019CombiningLiDARandTomoSARForestStructure.pdf:PDF},
    keywords = {SAR Processing, Forest, Biomass, LiDAR, SAR Tomography, Multibaseline SAR},
    owner = {ofrey},
    publisher = {Springer Science and Business Media {LLC}},
    
    }
    


  16. Massimiliano Pieraccini and Lapo Miccinesi. Ground-Based Radar Interferometry: A Bibliographic Review. Remote Sensing, 11(9):1029, April 2019.
    Abstract: Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. This article is a bibliographic review, as much complete as possible, of the scientific papers/articles published in the last 20 years, since the pioneering works in the nineties. Some statistics are reported here about the number of publications in the years, popularity of applications, operative modalities, operative bands. The aim of this review is also to identify directions and perspectives. In the opinion of authors, this type of radar systems will move forward faster modulations, wider view angle, MIMO (Multiple Input Multiple Output) systems and radar with capability to detect the vector of displacement and not only a single component.

    @Article{pieracciniMiccinesiRemoteSensing2019GroundBasedRadarInterferometryABibliographicReview,
    author = {Massimiliano Pieraccini and Lapo Miccinesi},
    journal = {Remote Sensing},
    title = {Ground-Based Radar Interferometry: A Bibliographic Review},
    year = {2019},
    month = {apr},
    number = {9},
    pages = {1029},
    volume = {11},
    abstract = {Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. This article is a bibliographic review, as much complete as possible, of the scientific papers/articles published in the last 20 years, since the pioneering works in the nineties. Some statistics are reported here about the number of publications in the years, popularity of applications, operative modalities, operative bands. The aim of this review is also to identify directions and perspectives. In the opinion of authors, this type of radar systems will move forward faster modulations, wider view angle, MIMO (Multiple Input Multiple Output) systems and radar with capability to detect the vector of displacement and not only a single component.},
    doi = {10.3390/rs11091029},
    file = {:pieracciniMiccinesiRemoteSensing2019GroundBasedRadarInterferometryABibliographicReview copy.pdf:PDF},
    owner = {ofrey},
    publisher = {{MDPI} {AG}},
    
    }
    


  17. Giuseppe Ruzza, Luigi Guerriero, Gerardo Grelle, Francesco Maria Guadagno, and Paola Revellino. Multi-Method Tracking of Monsoon Floods Using Sentinel-1 Imagery. Water, 11(11), 2019. Keyword(s): SAR Processing, Flood Mapping, Sentinel-1, Water.
    Abstract: Floods cause great losses in terms of human life and damages to settlements. Since the exposure is a proxy of the risk, it is essential to track flood evolution. The increasing availability of Synthetic Aperture Radar (SAR) imagery extends flood tracking capabilities because of its all-water and day/night acquisition. In this paper, in order to contribute to a better evaluation of the potential of Sentinel-1 SAR imagery to track floods, we analyzed a multi-pulse flood caused by a typhoon in the Camarines Sur Province of Philippines between the end of 2018 and the beginning of 2019. Multiple simple classification methods were used to track the spatial and temporal evolution of the flooded area. Our analysis indicates that Valley Emphasis based manual threshold identification, Otsu methodology, and K-Means Clustering have the potential to be used for tracking large and long-lasting floods, providing similar results. Because of its simplicity, the K-Means Clustering algorithm has the potential to be used in fully automated operational flood monitoring, also because of its good performance in terms of computation time.

    @Article{ruzzaGuerrieroGrelleGuadagnoRevellinoWATER2019Sentinel1MonsoonFloodsMapping,
    author = {Ruzza, Giuseppe and Guerriero, Luigi and Grelle, Gerardo and Guadagno, Francesco Maria and Revellino, Paola},
    title = {Multi-Method Tracking of Monsoon Floods Using Sentinel-1 Imagery},
    journal = {Water},
    year = {2019},
    volume = {11},
    number = {11},
    issn = {2073-4441},
    abstract = {Floods cause great losses in terms of human life and damages to settlements. Since the exposure is a proxy of the risk, it is essential to track flood evolution. The increasing availability of Synthetic Aperture Radar (SAR) imagery extends flood tracking capabilities because of its all-water and day/night acquisition. In this paper, in order to contribute to a better evaluation of the potential of Sentinel-1 SAR imagery to track floods, we analyzed a multi-pulse flood caused by a typhoon in the Camarines Sur Province of Philippines between the end of 2018 and the beginning of 2019. Multiple simple classification methods were used to track the spatial and temporal evolution of the flooded area. Our analysis indicates that Valley Emphasis based manual threshold identification, Otsu methodology, and K-Means Clustering have the potential to be used for tracking large and long-lasting floods, providing similar results. Because of its simplicity, the K-Means Clustering algorithm has the potential to be used in fully automated operational flood monitoring, also because of its good performance in terms of computation time.},
    article-number = {2289},
    doi = {10.3390/w11112289},
    file = {:ruzzaGuerrieroGrelleGuadagnoRevellinoWATER2019Sentinel1MonsoonFloodsMapping.pdf:PDF},
    keywords = {SAR Processing, Flood Mapping, Sentinel-1, Water},
    owner = {ofrey},
    url = {https://www.mdpi.com/2073-4441/11/11/2289},
    
    }
    


  18. N. Sakar, M. Rodriguez-Cassola, P. Prats-Iraola, and A. Moreira. Azimuth Reconstruction Algorithm for Multistatic SAR Formations With Large Along-Track Baselines. IEEE Transactions on Geoscience and Remote Sensing, pp 1-10, 2019. Keyword(s): Azimuth, Synthetic aperture radar, Image reconstruction, History, Receivers, Doppler effect, Reconstruction algorithms, Digital beamforming, high-resolution wide-swath (HRWS) radar, multistatic radar signal processing, synthetic aperture radar (SAR).
    Abstract: A multistatic synthetic aperture radar (SAR) system offers the potential of exceeding the capabilities of conventional SARs in various ways, one of which is to realize high-resolution imaging over wide swaths when operated under the Nyquist frequency. Due to the decrease of the operational pulse repetition frequency, the Doppler spectrum of the received data of the single channels appears strongly aliased and needs to be resolved via azimuth reconstruction. Our aim in this article is to suggest an accurate reconstruction strategy that is applicable to multistatic SAR systems also with large along-track baselines and very high resolution on curved orbits. The algorithm, which can be regarded as a generalized reconstruction in the range-Doppler domain, operates in two steps and is capable of correcting most of the polychromatic deviations over large areas, achieving accurate reconstruction in constellations with kilometric baselines, resolutions of about 15 lambda over swaths of hundreds of kilometers. The validity of our approach has been tested using point targets in two- and six-receiver multistatic configurations.

    @Article{sakarRodriguezPratsMoreiraTGRS2019AzimuthReconstructionMultistaticSARWithLargeAlongTrackBaselines,
    author = {N. {Sakar} and M. {Rodriguez-Cassola} and P. {Prats-Iraola} and A. {Moreira}},
    title = {Azimuth Reconstruction Algorithm for Multistatic SAR Formations With Large Along-Track Baselines},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    pages = {1-10},
    issn = {1558-0644},
    abstract = {A multistatic synthetic aperture radar (SAR) system offers the potential of exceeding the capabilities of conventional SARs in various ways, one of which is to realize high-resolution imaging over wide swaths when operated under the Nyquist frequency. Due to the decrease of the operational pulse repetition frequency, the Doppler spectrum of the received data of the single channels appears strongly aliased and needs to be resolved via azimuth reconstruction. Our aim in this article is to suggest an accurate reconstruction strategy that is applicable to multistatic SAR systems also with large along-track baselines and very high resolution on curved orbits. The algorithm, which can be regarded as a generalized reconstruction in the range-Doppler domain, operates in two steps and is capable of correcting most of the polychromatic deviations over large areas, achieving accurate reconstruction in constellations with kilometric baselines, resolutions of about 15 lambda over swaths of hundreds of kilometers. The validity of our approach has been tested using point targets in two- and six-receiver multistatic configurations.},
    doi = {10.1109/TGRS.2019.2950963},
    keywords = {Azimuth;Synthetic aperture radar;Image reconstruction;History;Receivers;Doppler effect;Reconstruction algorithms;Digital beamforming;high-resolution wide-swath (HRWS) radar;multistatic radar signal processing;synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  19. Muhammad Adnan Siddique, Tazio Strozzi, Irena Hajnsek, and Othmar Frey. A Case Study on the Correction of Atmospheric Phases for SAR Tomography in Mountainous Regions. IEEE Trans. Geosci. Remote Sens., 57(1):416-431, January 2019. 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, synthetic aperture radar, tomography, 3-D point cloud retrieval, SAR tomography based 3-D point cloud extraction, high-resolution spaceborne SAR, Cosmo SkyMed, Matter Valley, Switzerland, Alps, mountainous terrain, layover, layover separation, interferometric stack, layover scenario case, persistent scatterer interferometry, PSI, point-like scatterer, processing approach, Spaceborne radar, Synthetic aperture radar, Three-dimensional displays, Tomography, 3-D point cloud, SAR interferometry, deformation, displacement, subsidence, detection, radar interferometry, displacement mapping, spaceborne SAR, differential interferometry, differential tomography, coherent scatterer detection.
    Abstract: Synthetic aperture radar (SAR) tomography with repeat-pass acquisitions generally requires a priori phase calibration of the interferometric data stack by compensating for the atmosphere-induced phase delay variations. These variations act as a disturbance in tomographic focusing. In mountainous regions, the mitigation of these disturbances is particularly challenging due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. In this paper, we assess a data-driven approach to estimate these phase variations under a regression-kriging framework. The vertical stratification of the troposphere is modeled functionally while the impact of spatial turbulence is considered in a stochastic sense. The methodology entails an initial persistent scatterer interferometry (PSI) analysis. The atmospheric phases isolated for the persistent scatterers (PS) within the PSI processing are considered as samples of the 3-D distribution of the phase delay variations over the scene. These atmospheric phases are regressed against the spatial coordinates in map geometry at PS locations. In turn, kriging predictions are obtained at each location along the elevation profile where tomographic focusing is intended. A key point of this approach is that the requisite atmospheric corrections are incorporated within the tomographic focusing model. A case study has been performed on a data stack comprising 32 Cosmo-SkyMed stripmap images acquired over the Matter Valley in the Swiss Alps, in the summers of 2008-2013. The results show locally improved deformation sampling with tomographic methods compared to the initial PSI solution, primarily due to the improved phase calibration. In general, the work underscores the indispensability of height-dependent correction of atmospheric phases for SAR tomography.

    @Article{siddiqueStrozziHajnsekFreyTGRS2019AtmoCorrectionTomoPsiMountains,
    author = {Siddique, Muhammad Adnan and Strozzi, Tazio and Hajnsek, Irena and Frey, Othmar},
    title = {A Case Study on the Correction of Atmospheric Phases for {SAR} Tomography in Mountainous Regions},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2019},
    volume = {57},
    number = {1},
    pages = {416-431},
    month = jan,
    abstract = {Synthetic aperture radar (SAR) tomography with repeat-pass acquisitions generally requires a priori phase calibration of the interferometric data stack by compensating for the atmosphere-induced phase delay variations. These variations act as a disturbance in tomographic focusing. In mountainous regions, the mitigation of these disturbances is particularly challenging due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. In this paper, we assess a data-driven approach to estimate these phase variations under a regression-kriging framework. The vertical stratification of the troposphere is modeled functionally while the impact of spatial turbulence is considered in a stochastic sense. The methodology entails an initial persistent scatterer interferometry (PSI) analysis. The atmospheric phases isolated for the persistent scatterers (PS) within the PSI processing are considered as samples of the 3-D distribution of the phase delay variations over the scene. These atmospheric phases are regressed against the spatial coordinates in map geometry at PS locations. In turn, kriging predictions are obtained at each location along the elevation profile where tomographic focusing is intended. A key point of this approach is that the requisite atmospheric corrections are incorporated within the tomographic focusing model. A case study has been performed on a data stack comprising 32 Cosmo-SkyMed stripmap images acquired over the Matter Valley in the Swiss Alps, in the summers of 2008-2013. The results show locally improved deformation sampling with tomographic methods compared to the initial PSI solution, primarily due to the improved phase calibration. In general, the work underscores the indispensability of height-dependent correction of atmospheric phases for SAR tomography.},
    doi = {10.1109/TGRS.2018.2855101},
    file = {:siddiqueStrozziHajnsekFreyTGRS2019AtmoCorrectionTomoPsiMountains.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, synthetic aperture radar;tomography;3-D point cloud retrieval; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne SAR, Cosmo SkyMed, Matter Valley, Switzerland, Alps, mountainous terrain, layover, layover separation, interferometric stack;layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry, deformation, displacement, subsidence, detection, radar interferometry; displacement mapping; spaceborne SAR; differential interferometry; differential tomography, coherent scatterer detection},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueStrozziHajnsekFreyTGRS2018AtmoCorrectionTomoPsiMountains.pdf},
    
    }
    


  20. Ladina Steiner, Michael Meindl, and Alain Geiger. Characteristics and limitations of GPS L1 observations from submerged antennas. Journal of Geodesy, 93(2):267-280, February 2019. Keyword(s): GNSS, GPS, Snow-water equivalent, SWE, Submerged antennas.
    Abstract: Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.

    @Article{steinerMeindlGeigerJGeodesy2019GNSSL1observationsSubmergedAntennas,
    author = {Steiner, Ladina and Meindl, Michael and Geiger, Alain},
    title = {Characteristics and limitations of GPS L1 observations from submerged antennas},
    journal = {Journal of Geodesy},
    year = {2019},
    volume = {93},
    number = {2},
    pages = {267--280},
    month = feb,
    issn = {1432-1394},
    abstract = {Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.},
    day = {01},
    doi = {10.1007/s00190-018-1147-x},
    file = {:steinerMeindlGeigerJGeodesy2019GNSSL1observationsSubmergedAntennas.pdf:PDF},
    keywords = {GNSS, GPS, Snow-water equivalent, SWE, Submerged antennas},
    owner = {ofrey},
    url = {https://doi.org/10.1007/s00190-018-1147-x},
    
    }
    


  21. Stefano Tebaldini, Dinh Ho Tong Minh, Mauro Mariotti d'Alessandro, Ludovic Villard, Thuy Le Toan, and Jerome Chave. The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests. Surveys in Geophysics, May 2019. Keyword(s): SAR Processing, SAR Tomography, BIOMASS, Earth Explorer 7, EE7, Airborne radar, Array signal processing, Capon, Capon beamformer, L-band, P-band, SAR processing, SAR tomography, beamforming, Focusing, forestry, interferometry, InSAR, multibaseline, multiple signal classification, MUSIC, polarimetry, Remote Sensing, synthetic aperture radar, SAR, scattering, three-dimensional imaging, 3-D imaging, time-domain back-projection, TDBP, tomography, Vegetation, Spaceborne SAR.
    Abstract: Synthetic aperture radar (SAR) tomography (TomoSAR) is an emerging technology to image the 3D structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. The research on the use of P-band waves, in particular, has been largely propelled since 2007 in experimental studies supporting the future spaceborne Mission BIOMASS, to be launched in 2022 with the aim of mapping forest aboveground biomass (AGB) accurately and globally. The results obtained in the frame of these studies demonstrated that TomoSAR can be used for accurate retrieval of geophysical variables such as forest height and terrain topography and, especially in the case of dense tropical forests, to provide a more direct link to AGB. This paper aims at providing the reader with a comprehensive understanding of TomoSAR and its application for remote sensing of forested areas, with special attention to the case of tropical forests. We will introduce the basic physical principles behind TomoSAR, present the most relevant experimental results of the last decade, and discuss the potentials of BIOMASS tomography.

    @Article{tebaldiniEtAlSurveyInGeophysics2019SARTomographyTropicalForestReviewPaper,
    author = {Tebaldini, Stefano and Ho Tong Minh, Dinh and Mariotti d'Alessandro, Mauro and Villard, Ludovic and Le Toan, Thuy and Chave, Jerome},
    title = {The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in {SAR} Tomography of Tropical Forests},
    journal = {Surveys in Geophysics},
    year = {2019},
    month = {May},
    issn = {1573-0956},
    abstract = {Synthetic aperture radar (SAR) tomography (TomoSAR) is an emerging technology to image the 3D structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. The research on the use of P-band waves, in particular, has been largely propelled since 2007 in experimental studies supporting the future spaceborne Mission BIOMASS, to be launched in 2022 with the aim of mapping forest aboveground biomass (AGB) accurately and globally. The results obtained in the frame of these studies demonstrated that TomoSAR can be used for accurate retrieval of geophysical variables such as forest height and terrain topography and, especially in the case of dense tropical forests, to provide a more direct link to AGB. This paper aims at providing the reader with a comprehensive understanding of TomoSAR and its application for remote sensing of forested areas, with special attention to the case of tropical forests. We will introduce the basic physical principles behind TomoSAR, present the most relevant experimental results of the last decade, and discuss the potentials of BIOMASS tomography.},
    day = {16},
    doi = {10.1007/s10712-019-09539-7},
    file = {:tebaldiniEtAlSurveyInGeophysics2019SARTomographyTropicalForestReviewPaper.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography,BIOMASS, Earth Explorer 7, EE7,Airborne radar, Array signal processing, Capon, Capon beamformer, L-band, P-band, SAR processing, SAR tomography, beamforming, Focusing, forestry, interferometry, InSAR, multibaseline, multiple signal classification, MUSIC, polarimetry, Remote Sensing, synthetic aperture radar, SAR, scattering, three-dimensional imaging, 3-D imaging, time-domain back-projection, TDBP, tomography, Vegetation, Spaceborne SAR},
    owner = {ofrey},
    url = {https://doi.org/10.1007/s10712-019-09539-7},
    
    }
    


  22. Jan Torgrimsson, Patrick Dammert, Hans Hellsten, and Lars M. H. Ulander. SAR Processing Without a Motion Measurement System. IEEE Transactions on Geoscience and Remote Sensing, 57(2):1025-1039, February 2019. Keyword(s): SAR Processsing, Backprojection, Fast-factorized Back-projection, FFBP, Time-Domain Back-Projection, TDBP, Azimuth Focusing, Motion Compensation, MoComp, autofocus, geometric autofocus, radar imaging, synthetic aperture radar, synthetic aperture radar image, very high frequency band, base-2 fast factorized back-projection, track velocity error, CARABAS II system, ultrawideband data sets, innovative autofocus concept, subaperture pair, free geometry parameters, back-projection formulation, factorized geometrical autofocus, SAR processing, FGA algorithm, VHF-band, wavelength-resolution SAR image, FGA images, linear equidistant track, basic geometry model, Geometry, Synthetic aperture radar, Global Positioning System, Tracking, Apertures, Radar tracking, Autofocus, back-projection (BP), factorized geometrical autofocus (FGA), Synthetic Aperture Radar (SAR).
    Abstract: This paper leads a discussion on how to form a Synthetic Aperture Radar (SAR) image without knowing the relative track. That is, within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection (FFBP) formulation with six free geometry parameters (per subaperture pair). These are tuned step by step until a sharp image is obtained. This innovative autofocus concept can compensate completely for an erroneous geometry. The FGA algorithm has been applied successfully on two ultrawideband (UWB) data sets, acquired by the CARABAS II system at very high frequency (VHF)-band. The relative tracks are known (measured accurately). We, however, adopt and modify a basic geometry model. A linear equidistant track at fixed altitude is initially assumed. Apart from deviations due to linearization, a ~2.5-m/s along-track velocity error is also introduced. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a wavelength-resolution SAR image at VHF-band without support from a motion measurement system. The execution time for the examples in this paper is about five times longer with autofocus than without. Hence, the FGA algorithm is now fit for use on a regular basis.

    @Article{torgrimssonDammertHellstenUlanderTGRS2019SARProcessingGeometricFFBPWithoutMotionMeasurementSystem,
    author = {Torgrimsson, Jan and Dammert, Patrick and Hellsten, Hans and Ulander, Lars M. H.},
    title = {{SAR} Processing Without a Motion Measurement System},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    volume = {57},
    number = {2},
    pages = {1025-1039},
    month = feb,
    issn = {0196-2892},
    abstract = {This paper leads a discussion on how to form a Synthetic Aperture Radar (SAR) image without knowing the relative track. That is, within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection (FFBP) formulation with six free geometry parameters (per subaperture pair). These are tuned step by step until a sharp image is obtained. This innovative autofocus concept can compensate completely for an erroneous geometry. The FGA algorithm has been applied successfully on two ultrawideband (UWB) data sets, acquired by the CARABAS II system at very high frequency (VHF)-band. The relative tracks are known (measured accurately). We, however, adopt and modify a basic geometry model. A linear equidistant track at fixed altitude is initially assumed. Apart from deviations due to linearization, a ~2.5-m/s along-track velocity error is also introduced. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a wavelength-resolution SAR image at VHF-band without support from a motion measurement system. The execution time for the examples in this paper is about five times longer with autofocus than without. Hence, the FGA algorithm is now fit for use on a regular basis.},
    doi = {10.1109/TGRS.2018.2864243},
    file = {:torgrimssonDammertHellstenUlanderTGRS2019SARProcessingGeometricFFBPWithoutMotionMeasurementSystem.pdf:PDF},
    keywords = {SAR Processsing, Backprojection, Fast-factorized Back-projection, FFBP, Time-Domain Back-Projection, TDBP, Azimuth Focusing, Motion Compensation, MoComp, autofocus, geometric autofocus, radar imaging;synthetic aperture radar;synthetic aperture radar image;very high frequency band;base-2 fast factorized back-projection;track velocity error;CARABAS II system;ultrawideband data sets;innovative autofocus concept;subaperture pair;free geometry parameters;back-projection formulation;factorized geometrical autofocus;SAR processing;FGA algorithm;VHF-band;wavelength-resolution SAR image;FGA images;linear equidistant track;basic geometry model;Geometry;Synthetic aperture radar;Global Positioning System;Tracking;Apertures;Radar tracking;Autofocus;back-projection (BP);factorized geometrical autofocus (FGA);Synthetic Aperture Radar (SAR)},
    owner = {ofrey},
    
    }
    


  23. Karina Wilgan, Muhammad Adnan Siddique, Tazio Strozzi, Alain Geiger, and Othmar Frey. Comparison of Tropospheric Path Delay Estimates from GNSS and Space-Borne SAR Interferometry in Alpine Conditions. Remote Sensing, 11(15):1-24, July 2019. Note: 1789. Keyword(s): SAR Processing, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, interferometric stacking, multi-baseline interferometry, GNSS, GPS, Comparison, tropospheric path delay, Collocation, Kriging.
    Abstract: We compare tropospheric delays from Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) Interferometry (InSAR) in a challenging mountainous environment in the Swiss Alps, where strong spatial variations of the local tropospheric conditions are often observed.Tropospheric delays are usually considered to be an error for both GNSS and InSAR, and are typically removed. However, recently these delays are also recognized as a signal of interest, for example for assimilation into numerical weather models or climate studies. The GNSS and InSAR are techniques of complementary nature, as one has sparse spatial but high temporal resolution, and the other very dense spatial coverage but repeat pass of only a few days. This raises expectations for a combination of these techniques. For this purpose, a comprehensive comparison between the techniques must be first performed. Due to the relative nature of InSAR estimates, we compare the difference slant tropospheric delays (dSTD) retrieved from GNSS with the dSTDs estimated using Persistent ScattererInterferometry (PSI) of 32 COSMO-SkyMed SAR images taken in a snow-free period from June to October between 2008 and 2013. The GNSS estimates calculated at permanent geodetic stations are interpolated to the locations of persistent scatterers using an in-house developed least-squares collocation software COMEDIE. The Pearson's correlation coefficient between InSAR and GNSS estimates averaged over all acquisitions is equal to 0.64 and larger than 0.8 for approximately half of the layers. Better agreement is obtained mainly for days with high variability of the troposphere(relative to the tropospheric conditions at the time of the reference acquisition), expressed as standard deviations of the GNSS-based dSTDs. On the other hand, the most common feature for the days with poor agreement is represented by very stable, almost constant GNSS estimates. In addition,there is a weak correlation between the agreement and the water vapor values in the area, as well as with the number of stations in the closest vicinity of the study area. Adding low-cost L-1 only GPS stations located within the area of the study increases the biases for most of the dates, but the standard deviations between InSAR and GNSS decrease for the limited area with low-cost stations.

    @Article{wilganSiddiqueStrozziGeigerFreyRemoteSensing2019ComparisonTropoDelayFromGNSSandPSI,
    author = {Wilgan, Karina and Siddique, Muhammad Adnan and Strozzi, Tazio and Geiger, Alain and Frey, Othmar},
    title = {Comparison of Tropospheric Path Delay Estimates from {GNSS} and Space-Borne {SAR} Interferometry in Alpine Conditions},
    journal = {Remote Sensing},
    year = {2019},
    volume = {11},
    number = {15},
    pages = {1-24},
    month = {jul},
    note = {1789},
    abstract = {We compare tropospheric delays from Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) Interferometry (InSAR) in a challenging mountainous environment in the Swiss Alps, where strong spatial variations of the local tropospheric conditions are often observed.Tropospheric delays are usually considered to be an error for both GNSS and InSAR, and are typically removed. However, recently these delays are also recognized as a signal of interest, for example for assimilation into numerical weather models or climate studies. The GNSS and InSAR are techniques of complementary nature, as one has sparse spatial but high temporal resolution, and the other very dense spatial coverage but repeat pass of only a few days. This raises expectations for a combination of these techniques. For this purpose, a comprehensive comparison between the techniques must be first performed. Due to the relative nature of InSAR estimates, we compare the difference slant tropospheric delays (dSTD) retrieved from GNSS with the dSTDs estimated using Persistent ScattererInterferometry (PSI) of 32 COSMO-SkyMed SAR images taken in a snow-free period from June to October between 2008 and 2013. The GNSS estimates calculated at permanent geodetic stations are interpolated to the locations of persistent scatterers using an in-house developed least-squares collocation software COMEDIE. The Pearson's correlation coefficient between InSAR and GNSS estimates averaged over all acquisitions is equal to 0.64 and larger than 0.8 for approximately half of the layers. Better agreement is obtained mainly for days with high variability of the troposphere(relative to the tropospheric conditions at the time of the reference acquisition), expressed as standard deviations of the GNSS-based dSTDs. On the other hand, the most common feature for the days with poor agreement is represented by very stable, almost constant GNSS estimates. In addition,there is a weak correlation between the agreement and the water vapor values in the area, as well as with the number of stations in the closest vicinity of the study area. Adding low-cost L-1 only GPS stations located within the area of the study increases the biases for most of the dates, but the standard deviations between InSAR and GNSS decrease for the limited area with low-cost stations.},
    doi = {10.3390/rs11151789},
    file = {:wilganSiddiqueStrozziGeigerFreyRemoteSensing2019ComparisonTropoDelayFromGNSSandPSI.pdf:PDF},
    keywords = {SAR Processing, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, interferometric stacking, multi-baseline interferometry, GNSS, GPS, Comparison, tropospheric path delay, Collocation, Kriging},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/wilganSiddiqueStrozziGeigerFreyRemoteSensing2019ComparisonTropoDelayFromGNSSandPSI.pdf},
    publisher = {{MDPI} {AG}},
    
    }
    


  24. Pengfei Xie, Man Zhang, Lei Zhang, and Guanyong Wang. Residual Motion Error Correction with Backprojection Multisquint Algorithm for Airborne Synthetic Aperture Radar Interferometry. Sensors, 19(10), 2019. Keyword(s): SAR Processing, Time-Domain Back-Projection, Back-Projection, TDBP, Non-Linear Flight Tracks, Curvilinear SAR, digital elevation model, Airborne SAR, Motion Compensation, MoComp, Residual Motion Errors, Multisquint, Multi-aperture interferometry, MAI.
    Abstract: For airborne interferometric synthetic aperture radar (InSAR) data processing, it is essential to achieve precise motion compensation to obtain high-quality digital elevation models (DEMs). In this paper, a novel InSAR motion compensation method is developed, which combines the backprojection (BP) focusing and the multisquint (MSQ) technique. The algorithm is two-fold. For SAR image focusing, BP algorithm is applied to fully use the navigation information. Additionally, an explicit mathematical expression of residual motion error (RME) in the BP image is derived, which paves a way to integrating the MSQ algorithm in the azimuth spatial wavenumber domain for a refined RME correction. It is revealed that the proposed backprojection multisquint (BP-MSQ) algorithm exploits the motion error correction advantages of BP and MSQ simultaneously, which leads to significant improvements of InSAR image quality. Simulation and real data experiments are employed to illustrate the effectiveness of the proposed algorithm.

    @Article{xieZhangZhangWangRemoteSensing2019TDBPResidualMoCompMultiSquint,
    author = {Xie, Pengfei and Zhang, Man and Zhang, Lei and Wang, Guanyong},
    title = {Residual Motion Error Correction with Backprojection Multisquint Algorithm for Airborne Synthetic Aperture Radar Interferometry},
    journal = {Sensors},
    year = {2019},
    volume = {19},
    number = {10},
    issn = {1424-8220},
    abstract = {For airborne interferometric synthetic aperture radar (InSAR) data processing, it is essential to achieve precise motion compensation to obtain high-quality digital elevation models (DEMs). In this paper, a novel InSAR motion compensation method is developed, which combines the backprojection (BP) focusing and the multisquint (MSQ) technique. The algorithm is two-fold. For SAR image focusing, BP algorithm is applied to fully use the navigation information. Additionally, an explicit mathematical expression of residual motion error (RME) in the BP image is derived, which paves a way to integrating the MSQ algorithm in the azimuth spatial wavenumber domain for a refined RME correction. It is revealed that the proposed backprojection multisquint (BP-MSQ) algorithm exploits the motion error correction advantages of BP and MSQ simultaneously, which leads to significant improvements of InSAR image quality. Simulation and real data experiments are employed to illustrate the effectiveness of the proposed algorithm.},
    article-number = {2342},
    doi = {10.3390/s19102342},
    file = {:xieZhangZhangWangRemoteSensing2019TDBPResidualMoCompMultiSquint.pdf:PDF},
    keywords = {SAR Processing, Time-Domain Back-Projection, Back-Projection, TDBP, Non-Linear Flight Tracks, Curvilinear SAR, digital elevation model, Airborne SAR, Motion Compensation, MoComp, Residual Motion Errors, Multisquint, Multi-aperture interferometry, MAI},
    owner = {ofrey},
    url = {https://www.mdpi.com/1424-8220/19/10/2342},
    
    }
    


  25. M. Yang, P. Lopez-Dekker, P. Dheenathayalan, F. Biljecki, M. Liao, and R. F. Hanssen. Linking Persistent Scatterers to the Built Environment Using Ray Tracing on Urban Models. IEEE Transactions on Geoscience and Remote Sensing, 57(8):5764-5776, August 2019. Keyword(s): electromagnetic wave scattering, millimetre wave radar, radar imaging, ray tracing, specific physical objects, millimeter-scale displacements, satellite radar images, time series, coherent measurement points, urban models, fivefold-bounce scatterers, triple-bounce scatterers, identified scatterers, matched scatterers, ray tracing, point scatterers, ray-tracing synthetic aperture radar simulator, pointlike scatterers, Synthetic aperture radar, Solid modeling, Ray tracing, Scattering, Urban areas, Geometry, Object oriented modeling, Level of detail (LOD), persistent scatterers (PSs), ray tracing, simulation, synthetic aperture radar (SAR).
    Abstract: Persistent scatterers (PSs) are coherent measurement points obtained from time series of satellite radar images, which are used to detect and estimate millimeter-scale displacements of the terrain or man-made structures. However, associating these measurement points with specific physical objects is not straightforward, which hampers the exploitation of the full potential of the data. We have investigated the potential for predicting the occurrence and location of PSs using generic 3-D city models and ray-tracing methods, and proposed a methodology to match PSs to the pointlike scatterers predicted using RaySAR, a ray-tracing synthetic aperture radar simulator. We also investigate the impact of the level of detail (LOD) of the city models. For our test area in Rotterdam, we find that 10% and 37% of the PSs detected in a stack of TerraSAR-X data can be matched with point scatterers identified by ray tracing using LOD1 and LOD2 models, respectively. In the LOD1 case, most matched scatterers are at street level while LOD2 allows the identification of many scatterers on the buildings. Over half of the identified scatterers easily correspond to identify double or triple-bounce scatterers. However, a significant fraction corresponds to higher bounce levels, with approximately 25% being fivefold-bounce scatterers.

    @Article{yangLopezDekkerDheenathayalanBiljeckiLiaoHanssenTGRS2019LinkingPSItoBuiltupAreasUsingRayTracing,
    author = {M. {Yang} and P. {Lopez-Dekker} and P. {Dheenathayalan} and F. {Biljecki} and M. {Liao} and R. F. {Hanssen}},
    title = {Linking Persistent Scatterers to the Built Environment Using Ray Tracing on Urban Models},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2019},
    volume = {57},
    number = {8},
    pages = {5764-5776},
    month = {Aug},
    issn = {1558-0644},
    abstract = {Persistent scatterers (PSs) are coherent measurement points obtained from time series of satellite radar images, which are used to detect and estimate millimeter-scale displacements of the terrain or man-made structures. However, associating these measurement points with specific physical objects is not straightforward, which hampers the exploitation of the full potential of the data. We have investigated the potential for predicting the occurrence and location of PSs using generic 3-D city models and ray-tracing methods, and proposed a methodology to match PSs to the pointlike scatterers predicted using RaySAR, a ray-tracing synthetic aperture radar simulator. We also investigate the impact of the level of detail (LOD) of the city models. For our test area in Rotterdam, we find that 10% and 37% of the PSs detected in a stack of TerraSAR-X data can be matched with point scatterers identified by ray tracing using LOD1 and LOD2 models, respectively. In the LOD1 case, most matched scatterers are at street level while LOD2 allows the identification of many scatterers on the buildings. Over half of the identified scatterers easily correspond to identify double or triple-bounce scatterers. However, a significant fraction corresponds to higher bounce levels, with approximately 25% being fivefold-bounce scatterers.},
    doi = {10.1109/TGRS.2019.2901904},
    keywords = {electromagnetic wave scattering;millimetre wave radar;radar imaging;ray tracing;specific physical objects;millimeter-scale displacements;satellite radar images;time series;coherent measurement points;urban models;fivefold-bounce scatterers;triple-bounce scatterers;identified scatterers;matched scatterers;ray tracing;point scatterers;ray-tracing synthetic aperture radar simulator;pointlike scatterers;Synthetic aperture radar;Solid modeling;Ray tracing;Scattering;Urban areas;Geometry;Object oriented modeling;Level of detail (LOD);persistent scatterers (PSs);ray tracing;simulation;synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  26. Hao Zhang and Paco Lpez-Dekker. Persistent Scatterer Densification Through the Application of Capon- and APES-Based SAR Reprocessing Algorithms. IEEE Trans. Geosci. Remote Sens., pp 1-13, 2019. Keyword(s): SAR Processing, PSI, Persistent Scatterer Interferometry, Synthetic aperture radar, Signal resolution, Spatial resolution, Estimation, Dispersion, Jitter, Amplitude and phase estimation (APES), Capon, persistent scatterer (PS) density, PS interferometry (PSI), superresolution (SR)..
    Abstract: Capon's minimum-variance method (MVM) and amplitude and phase estimation (APES) spectral estimation algorithms can be applied to synthetic aperture radar (SAR) processing to improve the resolution and suppress sidelobe levels. In this paper, we use Capon-/APES-based SAR reprocessing algorithms to increase the persistent scatterer (PS) density in PS interferometry (PSI). We propose a PS candidate (PSC) selection algorithm applicable to the superresolution reprocessed images and the corresponding processing chain. The performance of the proposed algorithm is evaluated by a number of simulations and a stack of TerraSAR-X data. The results show that the Capon algorithm outperforms others in PSC selection. We present a full PSI time-series analysis on the PSCs extracted from the Capon-reprocessed stacks. The results show that the PS density is increased between 50% and 60%, while their interferometric quality is maintained.

    @Article{zhangLopezDekkerTGARS2019PSICaponAPES,
    author = {Zhang, Hao and L{\'o}pez-Dekker, Paco},
    title = {Persistent Scatterer Densification Through the Application of {Capon}- and {APES}-Based {SAR} Reprocessing Algorithms},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2019},
    pages = {1-13},
    issn = {0196-2892},
    abstract = {Capon's minimum-variance method (MVM) and amplitude and phase estimation (APES) spectral estimation algorithms can be applied to synthetic aperture radar (SAR) processing to improve the resolution and suppress sidelobe levels. In this paper, we use Capon-/APES-based SAR reprocessing algorithms to increase the persistent scatterer (PS) density in PS interferometry (PSI). We propose a PS candidate (PSC) selection algorithm applicable to the superresolution reprocessed images and the corresponding processing chain. The performance of the proposed algorithm is evaluated by a number of simulations and a stack of TerraSAR-X data. The results show that the Capon algorithm outperforms others in PSC selection. We present a full PSI time-series analysis on the PSCs extracted from the Capon-reprocessed stacks. The results show that the PS density is increased between 50% and 60%, while their interferometric quality is maintained.},
    doi = {10.1109/TGRS.2019.2913905},
    file = {:zhangLopezDekkerTGARS2019PSICaponAPES.pdf:PDF},
    keywords = {SAR Processing, PSI, Persistent Scatterer Interferometry, Synthetic aperture radar;Signal resolution;Spatial resolution;Estimation;Dispersion;Jitter;Amplitude and phase estimation (APES);Capon;persistent scatterer (PS) density;PS interferometry (PSI);superresolution (SR).},
    owner = {ofrey},
    
    }
    


Conference articles

  1. Roberto Coscione, Irena Hajnsek, and Othmar Frey. Trajectory Uncertainty in Repeat-Pass SAR Interferometry: A Case Study. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 338-341, 2019. Keyword(s): SAR Processing, Synthetic aperture radar (SAR), SAR interferometry, mobile mapping, car-borne SAR, UAV, airborne SAR, terrestrial radar interferometer, repeat-pass interferometry, differential interferometry, DInSAR, SAR imaging, INS, GNSS, GPS, Trajectory Uncertainty.
    Abstract: In the context of differential synthetic aperture radar interferometry (DInSAR), precise trajectory estimation of the SAR platform is necessary to minimize residual phase errors induced by inaccurate knowledge of the 3D acquisition geometry. Inertial navigation systems (INS) and global navigation satellite system (GNSS) are usually employed to track the position of the platform. However, their unavoidable inaccuracies lead to motion estimation errors that negatively affect the quality of the processed radar data.To assess the positioning performance in a repeat-pass scenario, we used a navigation-grade INS/GNSS system to precisely track the position and the attitude of a platform moving along a rail and carrying a SAR sensor. We analyse the performance of the positioning solution for different scenarios relevant to repeat-pass DInSAR. Since the position of the platform is nearly perfectly repeated at every pass (zero interferometric baseline), the precision of the estimated position can be assessed and the interferometric performance evaluated.

    @InProceedings{coscioneHajnsekFreyIGARSS2019INSGNSSNavAndDInSAR,
    author = {Coscione, Roberto and Hajnsek, Irena and Frey, Othmar},
    title = {Trajectory Uncertainty in Repeat-Pass {SAR} Interferometry: A Case Study},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2019},
    pages = {338-341},
    abstract = {In the context of differential synthetic aperture radar interferometry (DInSAR), precise trajectory estimation of the SAR platform is necessary to minimize residual phase errors induced by inaccurate knowledge of the 3D acquisition geometry. Inertial navigation systems (INS) and global navigation satellite system (GNSS) are usually employed to track the position of the platform. However, their unavoidable inaccuracies lead to motion estimation errors that negatively affect the quality of the processed radar data.To assess the positioning performance in a repeat-pass scenario, we used a navigation-grade INS/GNSS system to precisely track the position and the attitude of a platform moving along a rail and carrying a SAR sensor. We analyse the performance of the positioning solution for different scenarios relevant to repeat-pass DInSAR. Since the position of the platform is nearly perfectly repeated at every pass (zero interferometric baseline), the precision of the estimated position can be assessed and the interferometric performance evaluated.},
    doi = {10.1109/IGARSS.2019.8898809},
    file = {:coscioneHajnsekFreyIGARSS2019INSGNSSNavAndDInSAR.pdf:PDF},
    keywords = {SAR Processing, Synthetic aperture radar (SAR), SAR interferometry, mobile mapping, car-borne SAR, UAV,airborne SAR, terrestrial radar interferometer, repeat-pass interferometry, differential interferometry, DInSAR, SAR imaging, INS, GNSS, GPS, Trajectory Uncertainty},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/coscioneHajnsekFreyIGARSS2019INSGNSSNavAndDInSAR.pdf},
    
    }
    


  2. Othmar Frey, Charles L. Werner, and Roberto Coscione. Car-borne and UAV-borne mobile mapping of surface displacements with a compact repeat-pass interferometric SAR system at L-band. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 274-277, 2019. Keyword(s): SAR Processing, Synthetic aperture radar (SAR), SAR interferometry, mobile mapping, car-borne SAR, UAV, airborne SAR, terrestrial radar interferometer, repeat-pass interferometry, differential interferometry, DInSAR, SAR imaging, focusing, back-projection, Time-Domain Back-Projection, TDBP, GPU, CUDA, interferometry, L-band, INS, GNSS, GPS.
    Abstract: In this paper, we present first results of carborne and UAV-borne mobile mapping of potential surface displacements with a compact repeat-pass interferometric FMCW SAR system at L-band: (1) glacier-flow-induced displacements were measured at Stein glacier in the Swiss alps in car-borne mode along a slightly curved road section; (2) a valley slope was observed repeatedly using the vertical-take-off-and-landing (VTOL) UAV Scout B1-100 flown by Aeroscout. The SAR raw data were focused directly to an image grid in map coordinates, involving a digital elevation model and accurate GNSS/INS navigation data, by using a time-domain back-projection (TDBP) approach. These geocoded complex SAR images then allow to directly form differential interferograms in map coordinates. The feasibility of repeat-pass interferometry using our novel FMCW L-band SAR on mobile platforms such as a car or a UAV is successfully demonstrated with several data examples.

    @InProceedings{freyWernerCoscioneIGARSS2019CARandUAVborneDInSARLBand,
    author = {Frey, Othmar and Werner, Charles L. and Coscione, Roberto},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    title = {Car-borne and {UAV}-borne mobile mapping of surface displacements with a compact repeat-pass interferometric {SAR} system at {L}-band},
    year = {2019},
    pages = {274-277},
    abstract = {In this paper, we present first results of carborne and UAV-borne mobile mapping of potential surface displacements with a compact repeat-pass interferometric FMCW SAR system at L-band: (1) glacier-flow-induced displacements were measured at Stein glacier in the Swiss alps in car-borne mode along a slightly curved road section; (2) a valley slope was observed repeatedly using the vertical-take-off-and-landing (VTOL) UAV Scout B1-100 flown by Aeroscout. The SAR raw data were focused directly to an image grid in map coordinates, involving a digital elevation model and accurate GNSS/INS navigation data, by using a time-domain back-projection (TDBP) approach. These geocoded complex SAR images then allow to directly form differential interferograms in map coordinates. The feasibility of repeat-pass interferometry using our novel FMCW L-band SAR on mobile platforms such as a car or a UAV is successfully demonstrated with several data examples.},
    doi = {10.1109/IGARSS.2019.8897827},
    file = {:freyWernerCoscioneIGARSS2019CARandUAVborneDInSARLBand.pdf:PDF},
    keywords = {SAR Processing, Synthetic aperture radar (SAR), SAR interferometry, mobile mapping, car-borne SAR, UAV,airborne SAR, terrestrial radar interferometer, repeat-pass interferometry, differential interferometry, DInSAR, SAR imaging, focusing, back-projection,Time-Domain Back-Projection, TDBP, GPU, CUDA, interferometry, L-band, INS, GNSS, GPS},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerCoscioneIGARSS2019CARandUAVborneDInSARLBand.pdf},
    
    }
    


  3. Daniel Henke, Max Frioud, Julian Fagir, Sebastien Guillaume, Michael Meindl, Alain Geiger, S. Sieger, D. Janssen, F. Kloppel, M. Caris, S. Stanko, M. Renker, and Peter Wellig. Miranda35 Experiments in Preparation for Small UAV-Based SAR. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 8542-8545, July 2019. Keyword(s): airborne radar, autonomous aerial vehicles, CW radar, FM radar, Global Positioning System, image motion analysis, radar imaging, radar receivers, synthetic aperture radar, units (measurement), frequency-modulated continuous-wave synthetic aperture radar, energy efficiency, navigation data, inertial measurement unit, IMU, SAR image quality, airborne platform, SAR autofocus, small UAV-based SAR systems, FMCW SAR, Miranda35 experiments, moving baseline differential GPS, optical structure-from-motion-based localization, FHR FMCW MIRANDA35 sensor, Synthetic aperture radar, Global Positioning System, Radar polarimetry, Cameras, Optical sensors, SAR autofocus, navigation, synthetic aperture radar, small UAV.
    Abstract: Technological advances in frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) and the associated miniaturization and energy efficiency make it increasingly possible to transfer SAR systems from traditional airborne platforms to small UAVs. An important factor to successfully achieve high-quality imaging from SAR systems mounted on small drones is the precise knowledge of the platform's navigation data in best case by avoiding the use of an expensive and heavy inertial measurement unit (IMU). In this paper, we test different concepts and discuss the impact on SAR image quality using FHR's FMCW MIRANDA35 sensor. To compare several methods simultaneously on one platform and to have an IMU as reference, first preparatory steps were carried out on an airborne platform. Specifically, we present and evaluate solutions based on SAR autofocus, moving baseline differential GPS and optical structure-from-motion-based localization. SAR autofocus shows the best performance in our preliminary investigations.

    @InProceedings{henkeEtALIGARSS2019UAVMiranda35SAR,
    author = {Daniel Henke and Max Frioud and Julian Fagir and Sebastien Guillaume and Michael Meindl and Alain Geiger and S. {Sieger} and D. {Janssen} and F. {Kloppel} and M. {Caris} and S. {Stanko} and M. {Renker} and Peter Wellig},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    title = {{Miranda35} Experiments in Preparation for Small {UAV}-Based {SAR}},
    year = {2019},
    month = jul,
    pages = {8542-8545},
    abstract = {Technological advances in frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) and the associated miniaturization and energy efficiency make it increasingly possible to transfer SAR systems from traditional airborne platforms to small UAVs. An important factor to successfully achieve high-quality imaging from SAR systems mounted on small drones is the precise knowledge of the platform's navigation data in best case by avoiding the use of an expensive and heavy inertial measurement unit (IMU). In this paper, we test different concepts and discuss the impact on SAR image quality using FHR's FMCW MIRANDA35 sensor. To compare several methods simultaneously on one platform and to have an IMU as reference, first preparatory steps were carried out on an airborne platform. Specifically, we present and evaluate solutions based on SAR autofocus, moving baseline differential GPS and optical structure-from-motion-based localization. SAR autofocus shows the best performance in our preliminary investigations.},
    doi = {10.1109/IGARSS.2019.8897902},
    issn = {2153-7003},
    keywords = {airborne radar;autonomous aerial vehicles;CW radar;FM radar;Global Positioning System;image motion analysis;radar imaging;radar receivers;synthetic aperture radar;units (measurement);frequency-modulated continuous-wave synthetic aperture radar;energy efficiency;navigation data;inertial measurement unit;IMU;SAR image quality;airborne platform;SAR autofocus;small UAV-based SAR systems;FMCW SAR;Miranda35 experiments;moving baseline differential GPS;optical structure-from-motion-based localization;FHR FMCW MIRANDA35 sensor;Synthetic aperture radar;Global Positioning System;Radar polarimetry;Cameras;Optical sensors;SAR autofocus;navigation;synthetic aperture radar;small UAV},
    owner = {ofrey},
    
    }
    


  4. Laila Moreira, F. Castro, J. A. Goes, L. Bins, B. Teruel, J. Fracarolli, V. Castro, M. Alcantara, G. Ore, Dieter Luebeck, L. P. Oliveira, L. Gabrielli, and H. E. Hernandez-Figueroa. A Drone-borne Multiband DInSAR: Results and Applications. In 2019 IEEE Radar Conference (RadarConf), pages 1-6, April 2019. Keyword(s): SAR Processing, agriculture, cartography, geophysical techniques, radar imaging, radar interferometry, remote sensing, remote sensing by radar, synthetic aperture radar, tomography, change-detection maps, precision agriculture, subsurface tomography, cartography, low weight drone-borne SAR, foreseen applications, drone-borne multiband DInSAR, Synthetic Aperture Radar, powerful remote sensing tool, relevant products, cartographic system, Synthetic aperture radar, Radar antennas, Drones, Airborne radar, Agriculture, Tomography, SAR, remote sensing, drone-borne SAR.
    Abstract: Synthetic Aperture Radar (SAR) has become a powerful remote sensing tool during the last 25 years. Most relevant products are three dimensional and projected on a cartographic system: topographic, thematic and change-detection maps. Starting with the requirements of precision agriculture, subsurface tomography, subsidence and cartography a low weight drone-borne SAR was designed. It operates in P, L and C-bands with cross-track (InSAR) and differential Interferometry (DInSAR). The requirements of the foreseen applications, concept, design, results and validation from regular surveys and ground truths are presented.

    @InProceedings{moreiraEtAlRadarCon2019DroneBorneDInSAR,
    author = {Laila Moreira and F. {Castro} and J. A. Goes and L. {Bins} and B. {Teruel} and J. {Fracarolli} and V. {Castro} and M. {Alcantara} and G. {Ore} and Dieter Luebeck and L. P. {Oliveira} and L. {Gabrielli} and H. E. {Hernandez-Figueroa}},
    title = {A Drone-borne Multiband {DInSAR}: Results and Applications},
    booktitle = {2019 IEEE Radar Conference (RadarConf)},
    year = {2019},
    pages = {1-6},
    month = {April},
    abstract = {Synthetic Aperture Radar (SAR) has become a powerful remote sensing tool during the last 25 years. Most relevant products are three dimensional and projected on a cartographic system: topographic, thematic and change-detection maps. Starting with the requirements of precision agriculture, subsurface tomography, subsidence and cartography a low weight drone-borne SAR was designed. It operates in P, L and C-bands with cross-track (InSAR) and differential Interferometry (DInSAR). The requirements of the foreseen applications, concept, design, results and validation from regular surveys and ground truths are presented.},
    doi = {10.1109/RADAR.2019.8835653},
    file = {:moreiraEtAlRadarCon2019DroneBorneDInSAR.pdf:PDF},
    issn = {1097-5659},
    keywords = {SAR Processing, agriculture;cartography;geophysical techniques;radar imaging;radar interferometry;remote sensing;remote sensing by radar;synthetic aperture radar;tomography;change-detection maps;precision agriculture;subsurface tomography;cartography;low weight drone-borne SAR;foreseen applications;drone-borne multiband DInSAR;Synthetic Aperture Radar;powerful remote sensing tool;relevant products;cartographic system;Synthetic aperture radar;Radar antennas;Drones;Airborne radar;Agriculture;Tomography;SAR;remote sensing;drone-borne SAR},
    owner = {ofrey},
    
    }
    


  5. R. Rincon, B. Osmanoglu, P. Racette, Q. Bonds, M. Perrine, L. Brucker, S. Seufert, and C. Kielbasa. Tri-Frequency Synthetic Aperture Radar for the Measurements of Snow Water Equivalent. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 8653-8655, July 2019. Keyword(s): airborne radar, hydrological equipment, hydrological techniques, radiometers, snow, synthetic aperture radar, airborne synthetic aperture radar system, snow water equivalent, SWE, radiometer, active passive microwave system, frequency bands, successful system performance, tri-frequency synthetic aperture radar, SWESARR instrument, dual polarization radar, AD 2019 11, frequency 9.65 GHz, frequency 13.6 GHz, frequency 200.0 MHz, frequency 17.25 GHz, Snow, Spaceborne radar, Radar antennas, Synthetic aperture radar, Instruments, Microwave radiometry, Snow, SAR, SWE.
    Abstract: A new airborne synthetic aperture radar (SAR) system was recently developed for the estimation of snow water equivalent (SWE). The radar is part of the SWESARR (Snow Water Equivalent Synthetic Aperture Radar and Radiometer) instrument, an active passive microwave system specifically designed for the accurate estimation of SWE. The dual polarization (VV, VH) radar operates at three frequency bands (9.65 GHz, 13.6 GHz, and 17.25 GHz), with bandwidths of up to 200 MHz. The radar flew its first flight campaign in November 2019, along with SWESARR's -already operational - radiometer. The radar collected comprehensive data sets over various terrains that show a successful system performance. The instrument is slated to participate in future SnowEx campaigns.

    @InProceedings{rinconOsmanogluRacetteBondsPerrineBruckerSeufertKielbasaIGARSS2019SWESARRtriFreqSARforSWE,
    author = {R. {Rincon} and B. {Osmanoglu} and P. {Racette} and Q. {Bonds} and M. {Perrine} and L. {Brucker} and S. {Seufert} and C. {Kielbasa}},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    title = {Tri-Frequency Synthetic Aperture Radar for the Measurements of Snow Water Equivalent},
    year = {2019},
    month = jul,
    pages = {8653-8655},
    abstract = {A new airborne synthetic aperture radar (SAR) system was recently developed for the estimation of snow water equivalent (SWE). The radar is part of the SWESARR (Snow Water Equivalent Synthetic Aperture Radar and Radiometer) instrument, an active passive microwave system specifically designed for the accurate estimation of SWE. The dual polarization (VV, VH) radar operates at three frequency bands (9.65 GHz, 13.6 GHz, and 17.25 GHz), with bandwidths of up to 200 MHz. The radar flew its first flight campaign in November 2019, along with SWESARR's -already operational - radiometer. The radar collected comprehensive data sets over various terrains that show a successful system performance. The instrument is slated to participate in future SnowEx campaigns.},
    doi = {10.1109/IGARSS.2019.8900600},
    file = {:rinconOsmanogluRacetteBondsPerrineBruckerSeufertKielbasaIGARSS2019SWESARRtriFreqSARforSWE.pdf:PDF},
    issn = {2153-7003},
    keywords = {airborne radar;hydrological equipment;hydrological techniques;radiometers;snow;synthetic aperture radar;airborne synthetic aperture radar system;snow water equivalent;SWE;radiometer;active passive microwave system;frequency bands;successful system performance;tri-frequency synthetic aperture radar;SWESARR instrument;dual polarization radar;AD 2019 11;frequency 9.65 GHz;frequency 13.6 GHz;frequency 200.0 MHz;frequency 17.25 GHz;Snow;Spaceborne radar;Radar antennas;Synthetic aperture radar;Instruments;Microwave radiometry;Snow;SAR;SWE},
    owner = {ofrey},
    
    }
    


  6. Muhammad Adnan Siddique, Karina Wilgan, Tazzio Strozzi, Alain Geiger, Irena Hajnsek, and Othmar Frey. A Comparison of Tropospheric Path Delays estimated in PSI Processing against Delays Derived from a GNSS Network in the Swiss Alps. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 342-345, 2019. Keyword(s): SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, interferometric stacking, multi-baseline interferometry, GNSS, GPS, Comparison, tropospheric path delay, Collocation, Kriging.
    Abstract: This paper reports the first results of a comparative study of tropospheric delays retrieved by means of PSI processing of an interferometric stack of SAR images against those derived independently from a permanent GNSS network. The stack comprises 33 Cosmo-SkyMed stripmap images acquired in the summers between 2008-13 over the Matter Valley in the Swiss Alps. The long-term objective of the study is to explore whether GNSS-derived delays from existing networks (i.e., not deployed specifically for a test site) in Swiss Alpine regions can aid in tropospheric phase corrections in SAR data, or rather the phase corrections derived within the PSI processing being at a higher spatial resolution might be appropriate to build upon the GNSS products by improving their resolution.

    @InProceedings{siddiqueWilganStrozziGeigerHajnsekFreyIGARSS2019ComparisonTropoGNSSandInSAR,
    author = {Siddique, Muhammad Adnan and Wilgan, Karina and Strozzi, Tazzio and Geiger, Alain and Hajnsek, Irena and Frey, Othmar},
    title = {A Comparison of Tropospheric Path Delays estimated in {PSI} Processing against Delays Derived from a {GNSS} Network in the {Swiss} Alps},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2019},
    pages = {342-345},
    abstract = {This paper reports the first results of a comparative study of tropospheric delays retrieved by means of PSI processing of an interferometric stack of SAR images against those derived independently from a permanent GNSS network. The stack comprises 33 Cosmo-SkyMed stripmap images acquired in the summers between 2008-13 over the Matter Valley in the Swiss Alps. The long-term objective of the study is to explore whether GNSS-derived delays from existing networks (i.e., not deployed specifically for a test site) in Swiss Alpine regions can aid in tropospheric phase corrections in SAR data, or rather the phase corrections derived within the PSI processing being at a higher spatial resolution might be appropriate to build upon the GNSS products by improving their resolution.},
    doi = {10.1109/IGARSS.2019.8899799},
    file = {:siddiqueWilganStrozziGeigerHajnsekFreyIGARSS2019ComparisonTropoGNSSandInSAR.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, interferometric stacking, multi-baseline interferometry, GNSS, GPS, Comparison, tropospheric path delay, Collocation, Kriging},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWilganStrozziGeigerHajnsekFreyIGARSS2019ComparisonTropoGNSSandInSAR.pdf},
    
    }
    


  7. Dennis Valuyskiy, Sergey Vityazev, and Vladimir Vityazev. Resolution Improvement in Ground-Mapping Car-Borne Radar Imaging Systems. In 2019 IEEE International Conference on Imaging Systems and Techniques (IST), pages 1-5, December 2019. Keyword(s): SAR processing, carborne SAR, terrestrial radar interferometry, autofocus, phase gradient autofocus, image resolution, motion compensation, radar imaging, radar resolution, road vehicle radar, motion compensation technique, data acquisition, radar system, ground-mapping car-borne radar imaging systems, resolution improvement, Radar imaging, Electronics packaging, Data acquisition, Motion compensation, Radar antennas, Image resolution, radar imaging, PGA, autofocus, car-borne radar imaging, motion compensation, resolution improvement.
    Abstract: The problem of radar imaging is considered in this paper. An automobile is used as a platform for radar system mounting. It produces some special requirements for the data acquisition and processing, including the necessity for motion compensation. A motion compensation technique is offered in the paper and applied to the real-life data. The results demonstrate the efficiency of the suggested processing technique.

    @InProceedings{valuyskiyVityazevVityazevConf2019CarborneSARPhaseGradientAutofocus,
    author = {Valuyskiy, Dennis and Vityazev, Sergey and Vityazev, Vladimir},
    booktitle = {2019 IEEE International Conference on Imaging Systems and Techniques (IST)},
    title = {Resolution Improvement in Ground-Mapping Car-Borne Radar Imaging Systems},
    year = {2019},
    month = {Dec},
    pages = {1-5},
    abstract = {The problem of radar imaging is considered in this paper. An automobile is used as a platform for radar system mounting. It produces some special requirements for the data acquisition and processing, including the necessity for motion compensation. A motion compensation technique is offered in the paper and applied to the real-life data. The results demonstrate the efficiency of the suggested processing technique.},
    doi = {10.1109/IST48021.2019.9010537},
    file = {:valuyskiyVityazevVityazevConf2019CarborneSARPhaseGradientAutofocus.pdf:PDF},
    issn = {1558-2809},
    keywords = {SAR processing, carborne SAR, terrestrial radar interferometry, autofocus, phase gradient autofocus, image resolution;motion compensation;radar imaging;radar resolution;road vehicle radar;motion compensation technique;data acquisition;radar system;ground-mapping car-borne radar imaging systems;resolution improvement;Radar imaging;Electronics packaging;Data acquisition;Motion compensation;Radar antennas;Image resolution;radar imaging;PGA;autofocus;car-borne radar imaging;motion compensation;resolution improvement},
    
    }
    


  8. S. Wang, W. Feng, K. Kikuta, G. Chernyak, and M. Sato. Ground-Based Bistatic Polarimetric Interferometric Synthetic Aperture Radar System. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 8558-8561, July 2019. Keyword(s): radar imaging, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, ground-based bistatic polarimetric interferometric synthetic aperture radar system, novel ground-based bistatic polarimetric synthetic aperture radar system, Optical Electric Field Sensor, trihedral corner reflector, polarimetric capability, monostatic SAR images, bistatic polarimetric SAR images, 2D displacement estimation, displaceable corner reflector, Radar polarimetry, Estimation, Two dimensional displays, Synthetic aperture radar, Optical interferometry, Bistatic radar, Adaptive optics, Bistatic radar, radar polarimetry, radar interferometry, two-dimensional displacement, OEFS.
    Abstract: A novel ground-based bistatic polarimetric synthetic aperture radar (SAR) system using an Optical Electric Field Sensor (OEFS) as the receiver was developed for environmental studies. Fundamental experiments were carried out with a trihedral corner reflector (CR) as a target, showing the polarimetric capability of the system. Different polarization signatures from the monostatic SAR images were found by analyzing the bistatic polarimetric SAR images. Meanwhile, this system has the capability to estimate the two-dimensional (2D) displacement of the targets in the field of view. The simulation shows the feasibility and effectiveness of the 2D displacement estimation. The experimental results demonstrate that the accuracy along the x and y direction to the line of sight (LOS) based on the designed bistatic synthetic aperture radar system can reach millimeter level for the displaceable corner reflector.

    @InProceedings{wangFengKikutaChernyakSatoIGARSS2019TerrestrialBistaticPolInSARSystem,
    author = {S. {Wang} and W. {Feng} and K. {Kikuta} and G. {Chernyak} and M. {Sato}},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    title = {Ground-Based Bistatic Polarimetric Interferometric Synthetic Aperture Radar System},
    year = {2019},
    month = {July},
    pages = {8558-8561},
    abstract = {A novel ground-based bistatic polarimetric synthetic aperture radar (SAR) system using an Optical Electric Field Sensor (OEFS) as the receiver was developed for environmental studies. Fundamental experiments were carried out with a trihedral corner reflector (CR) as a target, showing the polarimetric capability of the system. Different polarization signatures from the monostatic SAR images were found by analyzing the bistatic polarimetric SAR images. Meanwhile, this system has the capability to estimate the two-dimensional (2D) displacement of the targets in the field of view. The simulation shows the feasibility and effectiveness of the 2D displacement estimation. The experimental results demonstrate that the accuracy along the x and y direction to the line of sight (LOS) based on the designed bistatic synthetic aperture radar system can reach millimeter level for the displaceable corner reflector.},
    doi = {10.1109/IGARSS.2019.8900455},
    file = {:wangFengKikutaChernyakSatoIGARSS2019TerrestrialBistaticPolInSARSystem.pdf:PDF},
    issn = {2153-7003},
    keywords = {radar imaging;radar interferometry;radar polarimetry;remote sensing by radar;synthetic aperture radar;ground-based bistatic polarimetric interferometric synthetic aperture radar system;novel ground-based bistatic polarimetric synthetic aperture radar system;Optical Electric Field Sensor;trihedral corner reflector;polarimetric capability;monostatic SAR images;bistatic polarimetric SAR images;2D displacement estimation;displaceable corner reflector;Radar polarimetry;Estimation;Two dimensional displays;Synthetic aperture radar;Optical interferometry;Bistatic radar;Adaptive optics;Bistatic radar;radar polarimetry;radar interferometry;two-dimensional displacement;OEFS},
    owner = {ofrey},
    
    }
    


  9. Charles L. Werner, Martin Suess, Othmar Frey, and Andreas Wiesmann. The ESA Wideband Microwave Scatterometer (WBSCAT): Design and Implementation. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 8339-8342, 2019. Keyword(s): ESA Snowlab, SnowScat, Wideband Scatterometer, WBScat, snow, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography.
    Abstract: WBSCAT is a new terrestrial 1-40 GHz polarimetric scatterometer. This instrument, built for the European Space Agency, with additional support from ETH WSL, is currently an element of the ESA SnowLab project for continuous microwave measurements of snowpack in Davos-Laret Switzerland. WBSCAT is based on a compact Vector Network Analyzer (VNA), combined with calibration standards and low-noise amplifiers to increase sensitivity. A pan/tilt positioner provides the angular and spatial diversity required for measurement of radar cross-section, 3D tomographic imaging, and measurements of interferometric coherence. The instrument can apply angular diversity and aperture synthesis to increase radiometric accuracy and suppress clutter. In Davos-Laret, WBSCAT is suspended from a 2.2-meter linear rail positioner that provides additional spatial diversity for high-resolution 3D tomographic imaging.

    @InProceedings{wernerSuessWegmullerFreyWiesmannIGARSS2019ESAWBScat,
    author = {Werner, Charles L. and Suess, Martin and Frey, Othmar and Wiesmann, Andreas},
    title = {The ESA Wideband Microwave Scatterometer (WBSCAT): Design and Implementation},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2019},
    pages = {8339-8342},
    abstract = {WBSCAT is a new terrestrial 1-40 GHz polarimetric scatterometer. This instrument, built for the European Space Agency, with additional support from ETH WSL, is currently an element of the ESA SnowLab project for continuous microwave measurements of snowpack in Davos-Laret Switzerland. WBSCAT is based on a compact Vector Network Analyzer (VNA), combined with calibration standards and low-noise amplifiers to increase sensitivity. A pan/tilt positioner provides the angular and spatial diversity required for measurement of radar cross-section, 3D tomographic imaging, and measurements of interferometric coherence. The instrument can apply angular diversity and aperture synthesis to increase radiometric accuracy and suppress clutter. In Davos-Laret, WBSCAT is suspended from a 2.2-meter linear rail positioner that provides additional spatial diversity for high-resolution 3D tomographic imaging.},
    doi = {10.1109/IGARSS.2019.8900459},
    file = {:wernerSuessWegmullerFreyWiesmannIGARSS2019ESAWBScat.pdf:PDF},
    keywords = {ESA Snowlab, SnowScat, Wideband Scatterometer, WBScat, snow, microwave scatterometer,aperture synthesis, time series, polarimetry, tomography, SAR tomography},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/wernerSuessWegmullerFreyWiesmannIGARSS2019ESAWBScat.pdf},
    
    }
    


  10. Andreas Wiesmann, Rafael Caduff, Charles L. Werner, Othmar Frey, Martin Schneebeli, Henning Lwe, Matthias Jaggi, Mike Schwank, Reza Naderpour, and Thorsten Fehr. ESA Snowlab Project: 4 Years of Wide Band Scatterometer Measurements of Seasonal Snow. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 5745-5748, 2019. Keyword(s): ESA Snowlab, SnowScat, Wideband Scatterometer, WBScat, snow, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography.
    Abstract: The aim of the ESA SnowLab project is to provide a comprehensive multi-frequency, multi-polarisation, multitemporal dataset of active microwave measurements over snow-covered grounds to investigate the relationship between effective snow- and ground parameters and the resultant signals detected by microwave radar. An important part for the development of microwave models is the microstructural characterisation. This characterisation can only be done by repeated measurements by SnowMicroPen and more completely, but also much more expensive, by X-ray micro-tomography. Within this project we complemented the microwave measurements of Alpine snow in Switzerland with extensive effective snow- and ground parameters and meteorological data. Microwave backscatter measurements were conducted using the 9-18 GHz ESA SnowScat instrument and since December 2018 the recently built ESA WBScat instrument. WBScat allows to extend the spectral coverage to 1-40 GHz.

    @InProceedings{wiesmannCaduffWernerFreySchneebeliLoeweJaggiSchwankNaderpourFehrIGARSS2019ESASnowlabOverview,
    author = {Wiesmann, Andreas and Caduff, Rafael and Werner, Charles L. and Frey, Othmar and Schneebeli, Martin and L{\"o}we, Henning and Jaggi, Matthias and Schwank, Mike and Naderpour, Reza and Fehr, Thorsten},
    title = {{ESA} {Snowlab} Project: 4 Years of Wide Band Scatterometer Measurements of Seasonal Snow},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2019},
    pages = {5745-5748},
    abstract = {The aim of the ESA SnowLab project is to provide a comprehensive multi-frequency, multi-polarisation, multitemporal dataset of active microwave measurements over snow-covered grounds to investigate the relationship between effective snow- and ground parameters and the resultant signals detected by microwave radar. An important part for the development of microwave models is the microstructural characterisation. This characterisation can only be done by repeated measurements by SnowMicroPen and more completely, but also much more expensive, by X-ray micro-tomography. Within this project we complemented the microwave measurements of Alpine snow in Switzerland with extensive effective snow- and ground parameters and meteorological data. Microwave backscatter measurements were conducted using the 9-18 GHz ESA SnowScat instrument and since December 2018 the recently built ESA WBScat instrument. WBScat allows to extend the spectral coverage to 1-40 GHz.},
    doi = {10.1109/IGARSS.2019.8898961},
    file = {:wiesmannCaduffWernerFreySchneebeliLoeweJaggiSchwankNaderpourFehrIGARSS2019ESASnowlabOverview.pdf:PDF},
    keywords = {ESA Snowlab, SnowScat, Wideband Scatterometer, WBScat, snow, microwave scatterometer,aperture synthesis, time series, polarimetry, tomography, SAR tomography},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/wiesmannCaduffWernerFreySchneebeliLoeweJaggiSchwankNaderpourFehrIGARSS2019ESASnowlabOverview.pdf},
    
    }
    


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