The tropospheric refraction along the signal path is the same for global navigation satellite systems (GNSS) and radar interferometry. However, different observation geometries, spatiotemporal sampling, signal processing methods, as well as signal wavelengths yield rather complementary measurements. The origin of this research is the question whether tropospheric delays retrieved at GNSS permanent stations can support persistent scatterer interferometry (PSI) processing for the retrieval of surface displacement in mountainous terrain, which is challenging because of spatial gaps due to radar layovers, shadowing, and temporal decorrelation in combination with strong variations of water vapor. We analyze maps of tropospheric path delays obtained by collocation of GNSS-estimated delays and PSI processing of an interferometric stack of Cosmo SkyMed X-band synthetic aperture radar (SAR) data in a mountainous region in Valais, Switzerland. We aim to assess the consistency and differences among the datasets to better understand their ability to sense small-scale structures in the lower atmosphere. In addition, we compare them with maps of tropospheric path delays derived from Consortium for Small-Scale Modelling (COSMO-2) numerical weather model (NWM) data. We investigate several factors affecting the interpolation of the GNSS zenith delays to the locations of the persistent scatterers, such as assumptions in the collocation, network size, and resolution. We assessed the meteorological parameters of the NWM to find potential correlations between specific meteorological conditions and different levels of (dis)agreement of delay maps; a clear correlation was not found. We found that the delays estimated from collocated GNSS measurements and PSI tend to have a different dependency on the terrain altitude. The PSI-derived path delays obtained from the X-band SAR data stack capture small-scale spatial variations also visible in NWM delay maps; whereas, at a larger scale, mismatches are found. It appears that the current GNSS network in the mountainous area of the Valais is not dense enough to capture strongly varying tropospheric refraction. We can conclude that denser networks (with a resolution of 5–10 km) in the interferometric SAR (InSAR) footprint region and a careful choice of the assumptions in our interpolation method would make GNSS more suitable for helping PSI processing.

This study investigates the potential of space-borne Synthetic Aperture Radar Interferometry for efficient detection of track anomalies using the Swiss Federal Railways (SBB) railway network as an example. The condition of the ballast substructure is crucial for track service life, and moisture accumulation is a primary cause of deterioration and can manifest itself by subsidence. Current operational methods for track condition assessment have limitations, and remote sensing techniques offer a promising alternative. Using a time-series of TerraSAR-X observations, we performed a persistent scatterer interferometry (PSI) analysis to estimate surface deformations and further analysed the deformation rates and variability along a 22km track section in Switzerland. The study explores the hypothesis that the variability of PSI-derived deformation estimates along the railway track can be related to longitudinal height measurements from track geometry vehicles. When compared with chord-based measurements from SBB, our preliminary results showed a promising correlation, suggesting that the variability in deformation measurements can indeed be linked to longitudinal height measurements obtained from track geometry vehicles. If proven effective, a satellite-based evaluation method could significantly reduce resources required for railway infrastructure maintenance.

In an agricultural river valley in central Idaho, USA, we conducted a case study to investigate interferometric synthetic aperture (InSAR) coherence and phase response as an indication of soil moisture change. Throughout a 3-day observational campaign, repeated observations were acquired from a mobile vehicle with a multi-polarization L-band (1.6 GHz) InSAR system, first prior to controlled irrigation and then during a dry-out period. Here, we present results that show the time series of coherence and phase in coordination with in-situ soil moisture observations at two depths over the three days of the controlled experiment. During the subsequent dry out period, the time series of interferometric coherence shows an immediate degradation of the signal with a subsequent improvement. The in-situ soil moisture observations highlight this transition of controlled irrigation to subsequent drying out of the soils. We anticipate future work to include investigation of the interferometric times series of phase change as it relates to quantitative changes in soil moisture.

Ground-motion-related geohazards are omnipresent in alpine areas. Time series of spaceborne SAR data are routinely used to assess surface displacement with large coverage. However, there are also many cases and expositions for which terrestrial radar systems are more suitable to obtain measurements of ground motion. Observing a mountain slope from a moving car or a UAV and thereby spanning a much longer synthetic aperture allows using also lower frequencies, such as L-band, with good spatial resolution. In addition, if aperture synthesis using a mobile mapping SAR system is employed at higher frequencies, the azimuth resolution can also be further improved compared to the azimuth resolution of (quasi-) stationary radar system at larger range distances of several kilometers. In this contribution, we report case studies that we are conducting to further develop and consolidate ground motion mapping by means of our car-borne DInSAR system as an operational application.

Time series of SAR tomographic profiling measurements of seasonal snow in the Swiss Alps were acquired with the tower-mounted ESA Wideband Scatterometer (WBScat) during an entire snow season as part of the ESA SnowLab campaign. The wide range of frequency bands (1-40 GHz) covered in combination with the depth-resolving capability of the tomographic SAR measurements provides new insights into relative change of location and intensity of radar backscatter within the snowpack during melting and refreezing cycles as a function of time and various parameters obtained by auxiliary measurements such as snow accumulation, snow mass (SWE), snow surface temperature, and liquid water content. It is found that at both, Ku-band and Ka-band, the tomographic profiles provide evidence of substantial backscatter at melt/freeze crust interfaces within the seasonal snowpack. Varying penetration depths and (re-)appearing backscattering layers can be observed throughout several cycles of snow melting and gradual refreezing.

We present the results of recent observations of terrestrial snow cover with KAPRI, a Ku-band polarimetric-interferometric radar system with bistatic capabilities. The bistatic configuration allows observation of phenomena which are not observable in the monostatic regime. Observations of polarization phase differences of snow cover on top of the Great Aletsch Glacier revealed that the behaviour of these parameters markedly varies between different times of year, as well as between the monostatic and bistatic acquisition modes. The bistatic capabilities of KAPRI were also recently used to characterize the coherent backscatter opposition effect (CBOE) in seasonal snow. We discuss the potential of such bistatic observations to observe quantities which are unobservable in the monostatic regime, and which could serve as new inputs for snow parameter retrieval methods.

Multistatic airborne synthetic aperture radar (MuA-SAR) systems can achieve high-resolution imaging in a short time by fusing observation data from multiple radar platforms. However, its imaging quality relies on a rigorous design of the spatial configuration (SC) of each platform, mainly including the relative spatial separation and velocity. The rigorously designed SCs make it difficult to obtain in actual flight and weaken the flexibility advantage brought by the airborne platforms. Therefore, it is meaningful and necessary to explore a new SC design method to obtain relaxed SCs under the condition of ensuring imaging quality. In this paper, to relax the limitations of SC, an optimal design method for MuA-SAR SC is proposed. First, the relationship between the spatial configuration, wavenumber spectrum (WS) distribution, and imaging performance is established, and it visually reveals the configuration limitations. Second, an optimized search space of SC is defined by the peak to sidelobe ratio (PSLR) to relax the space to compromised configurations. Finally, the SC design problem is transformed into a constrained multiple objective optimization problem (CMOP) which is solved by the multiple objective particle swarm optimization (MOPSO) algorithm. The simulation results show that the proposed method can still obtain the optimized SC beyond the strictly restricted configuration space, which expands the SC limitations of the MuA-SAR system.

The Ku-band provides opportunities for investigations of snow morphology through radar observations, since it exhibits a relatively high amount of scattering even from snow layers of limited depth, while maintaining low absorption. Due to technological and practical challenges, the bistatic parameter space of Ku-band radar observations of natural media such as snow, has been relatively unexplored. We present radar measurements of snow cover obtained with KAPRI, a bistatic polarimetric Ku-band radar system. In August 2021 and March 2022, we carried out time series observations of the Aletsch glacier in the Swiss Alps, acquiring a fully-polarimetric interferometric time series of both monostatic and simultaneous bistatic observations of the glacier's accumulation zone. This dataset will serve as a test-bed to investigate new snow parameter inversion methods based on bistatic Ku-band radar data. The bistatic polarimetric measurement configuration, as well as preliminary results of the analysis of radar backscatter, are presented.

This article presents the bistatic operation mode and the performance analysis of KAPRI, a terrestrial frequency-modulated continuous-wave (FMCW) Ku-band polarimetric radar interferometer capable of acquiring bistatic full-polarimetric datasets with high spatial and temporal resolution. In the bistatic configuration, the system is composed of two independently operating KAPRI devices, one serving as a primary transmitter and receiver and the other as a secondary receiver. The secondary bistatic dataset is affected by possible offsets between the two devices’ reference clocks, as well as distortions arising from the bistatic geometry. To correct for this, we present a two-chirp bistatic FMCW signal model, which accounts for the distortions, and a reference chirp transmission procedure, which allows correcting the clock offsets in the deramped signal time domain. The second challenge of operation of a bistatic polarimetric system is polarimetric calibration since it is not possible to employ purely monostatic targets such as corner reflectors. For this purpose, we developed a novel active calibration device Variable-Signature Polarimetric Active Radar Calibrator (VSPARC), designed for monostatic and bistatic calibration of all polarimetric channels. VSPARC and its associated novel polarimetric calibration method were then used to achieve full calibration of both KAPRI devices with polarimetric phase calibration accuracy of 20° and 30-dB polarization purity in field conditions. This article thus presents a complete measurement configuration and data processing pipeline necessary for synchronization, coregistration, and polarimetric calibration of bistatic and monostatic datasets acquired by a real-aperture FMCW radar.

WBSCAT is a polarimetric scatterometer developed for the European Space Agency for measuring microwave signatures of snow in support of the SnowLab and SnowLab-NG projects. SnowLab-NG includes feasibility studies for ESA candidate satellite missions operating at L-Band such as ROSE-L and Hydroterra. The WBSCAT instrument is based on a vector network analyzer to cover the 1–40 GHz frequency range, including L-Band. Using ground-based data collected in the near-field to model data collected by satellites is challenging when there is volume scattering from a thick layer such as snowpack. WBSCAT has been constructed to use near-field aperture synthesis to permit focusing of backscatter data. Focusing mitigates the effects of near-field operation by synthesizing a narrow antenna beam that illuminates a smaller volume of the snowpack. Using aperture synthesis, an improvement in azimuth resolution by a factor of 6 is possible with WBSCAT at L-band. Initial results from phase calibration of a calibration target response show the potential for this approach.

In this paper, we present examples of DInSAR-based measurement of surface displacements using a novel compact L-band SAR system that can be mounted on mobile mapping platforms such as a UAV or a car. The good DInSAR system performance is demonstrated and, particularly, we also show a use case in which a car-borne system setup is employed to map surface displacements of a fast-moving landslide and the surrounding area in Switzerland. Our results show that car-borne and UAV-borne interferometric displacement measurements at L-band are feasible with high quality over various natural terrain. This novel compact DInSAR system for agile platforms complements existing terrestrial, airborne, and space-borne radar interferometry systems in terms of its new combination of (1) radar wavelength (sensitivity to displacement/decorrelation properties), (2) spatial resolution, (3) (near-) terrestrial observation geometry, and (4) mobile mapping capability.

SAR offset tracking, applied on areas with strong temporal decorrelation, requires relatively large image templates for cross-correlation to compensate for incoherent radar speckle. Template edge lengths of 64–512 pixels are common. Furthermore, velocity maps are often incomplete because weakly visible features are obscured by uncorrelated speckle. To improve SAR offset tracking, we propose a new robust method which can significantly enhance both the spatial completeness and the resolution of velocity products by assuming a stationary velocity field. The method minimizes the motion blur of moving features which occurs when SAR backscatter time series are multilooked in time. Our velocity-adaptive temporal multilooking strongly reduces speckle without losing spatial resolution which makes the cross-correlation much more robust even for template sizes as small as 30 x 30 pixels. We demonstrate the method by generating a high resolution velocity map of Great Aletsch Glacier in Switzerland.

In this submission the bistatic operation mode of KAPRI, a polarimetric-interferometric, ground-based, real-aperture, Ku-band, FMCW radar is presented. Its possible configurations and the synchronization procedures needed to achieve distortion-free single-look complex bistatic images are described. The challenges of polarimetric calibration in the bistatic regime are outlined, and a novel active calibration device and the associated polarimetric calibration method which are used for bistatic calibration of KAPRI are presented. First results of observations of natural environments (vegetation, snow) using bistatic KAPRI are shown.

Terrestrial radar interferometry (TRI) can measure displacements at high temporal resolution, potentially with high accuracy. An application of this method is the observation of the surface flow velocity of steep, fast-flowing aglaciers. For these observations, the main factor limiting the accuracy of TRI observations is the spatial and temporal variabilities in the distribution of atmospheric water vapor content, causing a phase delay [atmospheric phase screen (APS)] whose magnitude is similar to the displacement phase. This contribution presents a geostatistical analysis of the spatial and temporal behaviors of the APS in Ku-Band TRI. The analysis is based on the assumption of a separable spatiotemporal covariance structure, which is tested empirically using variogram analysis. From this analysis, spatial and temporal APS statistics are estimated and used in a two-step procedure combining regression-Kriging with generalized least squares (GLS) inversion to estimate a velocity time-series. The performance of this method is evaluated by cross-validation using phase observations on stable scatterers. This analysis shows a considerable reduction in residual phase variance compared with the standard approach of combining the linear models of APS stratification and interferogram stacking.

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.

In this paper, we present first results of car-borne 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.

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.

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.

The aim of the ESA SnowLab project is to provide a comprehensive multi-frequency, multi-polarisation, multi-temporal 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.

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 the 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, this paper underscores the indispensability of height-dependent correction of atmospheric phases for SAR tomography.

A geostatistical analysis of the atmospheric phase screen (APS) affecting Ku-Band terrestrial radar interferometric (TRI) observations of a fast-flowing alpine glacier is made assuming a separable spatio-temporal covariance structure. Such a structure facilitates the mitigation of APS: the atmospheric phase affecting individual interferograms can be extrapolated form a set of persistent scatterers (PS) using regression-Kriging. After removing this estimate the residual APS is only correlated in time; its effect on surface displacement estimation is mitigated with a generalized least squares (GLS) inversion employing an estimate of the temporal covariance of the APS. The applicability of a separable covariance structure and the performance of the APS correction method are assessed on a TRI timeseries of Bisgletscher, a glacier in the southwestern Swiss Alps.

Repeat-pass differential SAR interferometry (DInSAR) using spaceborne SAR data or stationary terrestrial radar data is an established technique to measure surface displacements. However, repeat-pass DInSAR from agile platforms (airborne/car-borne) is challenging due to residual motion errors. This is particularly true for high-frequency radar where motion errors of few millimeters represent a non-negligible fraction of the wavelength. In this paper, an experimental car-borne SAR system is presented. Such a system is complementary to the existing solutions (namely spaceborne, airborne, and terrestrial systems) in terms of geometry of acquisition, and flexibility in the selection of temporal baselines and location of the acquisitions. To meet the need of consistent and precise trajectory information, proper postprocessing procedure must be applied to the raw positioning data collected from the inertial navigation system (INS) and the global positioning system (GNSS). A viable procedure is here presented and first results discussed.

As part of the ESA SnowLab campaign the SnowScat device, a terrestrial stepped-frequency continuous-wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz, was operated in tomographic profiling mode. In this tomographic profiling mode the SnowScat device is subsequently displaced in elevation direction to obtain a high-resolution not only in range direction but also along elevation. This leads to two-dimensional vertical profiles of a snowpack, which means that radar backscatter, co-polar phase difference, interferometric phase and coherence can be distinguished also along the vertical dimension of the snowpack. In this paper, we provide a summary and a few examples of a time series of tomographic measurements of snow obtained within the ESA SnowLab campaign at two different locations in the Swiss Alps during three snow seasons.

Terrestrial radar systems are used operationally for area-wide measurement and monitoring of surface displacements on steep slopes, as prevalent in mountainous areas or also in open pit mines. One limitation of these terrestrial systems is the decreasing cross-range resolution with increasing distance of observation due to the limited antenna size of the real aperture radar or the limited synthetic aperture of the quasi-stationary SAR systems. Recently, we have conducted a first experiment using a car-borne SAR system at Ku-band, demonstrating the time-domain back-projection (TDBP) focusing capability for the FMCW case and single-pass interferometric capability of our experimental Ku-band car-borne SAR system. The cross-range spatial resolution provided by such a car-based SAR system is potentially independent from the distance of observation, given that an adequate sensor trajectory can be built. In this paper, we give (1) an overview of the updated system hardware (radar setup and high-precision combined INS/GNSS positioning and attitude determination), and (2) present SAR imagery obtained with the updated prototype Ku-band car-borne SAR system.

Differential synthetic aperture radar (SAR) tomography allows separation of multiple coherent scatterers interfering in the same range-azimuth resolution cell as well as the estimation of the deformation parameters of each scatterer. In this way, the spatio-temporal tomographic inversion serves as a means to resolve the layover and simultaneously improve deformation sampling. Compared to metropolitan regions with several man-made structures, the prevalence of coherent scatterers in the villages of alpine regions is generally low, while at the same time layovers are widespread due to the ruggedness of the terrain. Moreover, the drastic height variations in the imaged scene necessitate height-dependent compensation of the atmospheric phase delay variations within the tomographic inversion. This paper addresses these concerns while performing experiments on an interferometric stack comprising 33 Cosmo-SkyMed strimap images acquired in the summers between 2008-13 over Matter Valley in the Swiss Alps. The results show improved deformation sampling along the layover-affected mountainside.

Differential interferometry using ground-based radar systems permits to monitor displacements in natural terrain with high flexibility in location, time of acquisition, and revisit time. In combination with polarimetric imaging, discrimination of different scattering mechanisms present in a resolution cell can be obtained simultaneously with the estimation of surface displacement. In this paper, we present the preprocessing steps and the calibration procedure required to produce high-quality calibrated polarimetric single-look complex imagery with KAPRI, a new portable Ku-band polarimetric radar interferometer. The processing of KAPRI data into single look complex images is addressed, including the correction of beam squint and of azimuthal phase variations. A polarimetric calibration model adapted to the acquisition mode is presented and used to produce calibrated polarimetric covariance matrix data. The methods are validated by means of a scene containing five trihedral corner reflectors. Data preprocessing is assessed by analyzing the oversampled response of a corner reflector, and the polarimetric calibration quality is verified by computing polarimetric signatures and residual calibration parameters.

SnowScat is a terrestrial stepped-frequency continuous-wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. Recently, the hardware has been upgraded by adding a tomographic profiling mode. This tomographic approach allows to retrieve high-resolution information about a snowpack via observables, such as radar backscatter, co-polar phase difference, interferometric phase and coherence. Since the tomographic imaging itself is also affected by the refraction occurring at the air-snow interface and within the snowpack the two problems, 1) the production of well-focused and correctly located tomographic profiles, and 2) the retrieval of snow structure parameters are inherently linked. In this contribution, a tomographic inversion scheme to retrieve the refractive index of snow through an autofocus approach is presented. The current autofocus-based retrieval relies on using an aluminium sphere of a test target deployed in the scene. The refractive indices and accompanying snow density measurements obtained at four dates during a cold period in January during the ESA SnowLab 2016/2017 campaign are compared to an empirical model by Matzler and Wiesmann that describes the relation between snow density and the real part of the relative permittivity for dry snow.

Differential SAR tomography is a means to resolve layover of temporally coherent scatterers while simultaneously estimating their elevation and average deformation. In alpine regions, drastic height variations result in frequent layovers which are rejected during typical persistent scatterer interferometric (PSI) analyses. In this paper, we explore the potential of tomographic techniques to improve deformation sampling in an alpine region of interest relative to a PSI-based deformation assessment. The mitigation of the atmospheric phase contributions, as required for both tomography and PSI, is often more involved in alpine regions due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. We assume a linear multivariate dependence of atmospheric phase on the spatial location and height of the scatterers, estimate it using universal/regression kriging and subsequently incorporate it within the tomographic focusing. Experiments are performed on an interferometric stack comprising of 32 Cosmo-SkyMed strimap images acquired in the summers of 2008-2013 over Mattervalley in the Swiss Alps.

An acknowledgement provided by the authors was lost during production for the above paper[1]. It is provided here as follows:

The SnowScat device is a ground-based stepped-frequency continuous-wave (SFCW) scatterometer supporting fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz. It was originally designed to support the investigation and validation of Snow Water Equivalent (SWE) retrieval algorithms in the context of the development of the deselected COld REgions Hydrology High-resolution Observatory (CoReH20) candidate Earth Explorer 7 mission. Recently, the SnowScat hardware has been enhanced to also provide a tomographic profiling mode which allows to obtain high-resolution 2-D vertical profiles that may provide further insight into the electromagnetic interaction within layered snow packs. In winter 2014/2015, a first test campaign was carried out yielding a successful proof of concept of the enhanced hardware, tomographic measurement, and basic processing concept. In Nov/Dec 2015, the SnowScat device was then installed as a part of the SnowLab experiment at a test site on 1700m altitude close to the Grimsel pass in Switzerland. A comprehensive time series of tomographic profiles of a snow pack was acquired until end of March, 2016. In this paper, we present and discuss first results of this new time series of tomographic profiles including 2-D vertical profiles of backscatter, phase difference between the co-polar channels, and interferometric phase difference.

SAR tomography can be used as an add-on to persistent scatterer interferometry (PSI) to increase deformation sampling in urban areas by resolving the frequently occurring layovers that are by definition rejected in the PSI processing. This paper, while focusing on the case of a typical high-rise building in layover, quantitatively assesses the potential gain in deformation sampling achieved by the added use of an advanced SAR tomographic technique relative to a PSI approach. At the same time, the quantity of the detected scatterers is weighed against their quality, as assessed on the basis of root-mean-square (RMS) phase deviation between the measurements and the model fit. The quality of the scatterers is also compared with the quality of the persistent scatterers as identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap mode images.

Sentinel-1 IWS interferometric time-series analysis (SBAS and PSI) is discussed and results over Mexico City, a mega-city subject to very substantial ground deformation, are presented. In the early steps the processing needs to be adapted to the organization of the data in sub-swaths and burst, and for the SLC co-registration an extremely accurate co-registration is required for interferometry, because of the strong along-track Doppler centroid variation. Furthermore, a deramping of the co-registered SLC for an along-track phase ramp present in each burst is applied. After that interferometric time-series techniques (SBAS, PSI) can be applied in the same way as for stripmap mode data.

Persistent scatterer interferometry (PSI) is in operational use for spaceborne synthetic aperture radar (SAR)-based deformation analysis. A limitation inherently associated with PSI is that, by definition, a persistent scatterer (PS) is a single dominant scatterer. Therefore, pixels containing signal contributions from multiple scatterers, as in the case of a layover, are typically rejected in the PSI processing, which in turn limits deformation retrieval. SAR tomography has the ability to resolve layovers. This paper investigates the added value that can be achieved by operationally combining SAR tomography with a PSI approach toward the objective of improving deformation sampling in layover-affected urban areas. Different tomographic phase models are implemented and compared as regards their suitability in resolving layovers. Single-look beamforming-based tomographic inversion and a generalized likelihood ratio test (GLRT)-based detection strategy are used to detect single and double scatterers. The quantity of the detected scatterers is weighed against their quality as defined in terms of the phase deviation between the single-look complex (SLC) measurements and the tomographic model fit. The gain in deformation sampling that can be derived with tomography relative to a PSI-based analysis is quantitatively assessed, and alongside the quality of the scatterers obtained with tomography is compared with the quality of the PSs identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap images. The results obtained show that, although there is a tradeoff between the quantity and the quality of the detected scatterers, the tested SAR tomography approach leads to an improvement in deformation sampling in layover-affected areas.

Persistent scatterer interferometry (PSI) assumes the presence of a single temporally coherent scatterer in a range-azimuth pixel. Multiple scatterers interfering in the same pixel, as for the case of a layover, are typically rejected. Conventional SAR tomography (3D SAR) is a means to separate the individual scatterers in layover. Advanced tomographic inversion approaches employing extended phase models additionally allow simultaneous retrieval of scatterer elevation and deformation parameters. In this way, SAR tomography can increase deformation sampling and thereby complement a PSI-based analysis. This paper investigates the use of tomography as an add-on to PSI for spatio-temporal inversion of single and double scatterers in urban areas. Results are provided on an interferometric stack of 50 stripmap TerraSAR-X images acquired over the city of Barcelona.

SAR tomography as an extension to persistent scatterer interferometry (PSI) approaches has the potential to improve the level of detail of retrievable information, in particular, in the case of layover scenarios in urban areas. In this paper, a processing approach is sketched that eventually allows for retrieving a 3-D point cloud of point-like scatterers based on subsequent PSI and SAR tomography processing of an interferometric stack of high-resolution spaceborne TerraSAR-X data acquired over the city of Barcelona between the years 2008 and 2012. Experimental results are presented in the form of (1) vertical tomographic slices of high-rise buildings and (2) a 3-D point cloud of a larger district of the city of Barcelona retrieved from the tomograms.

Agile SAR platforms such as an automobile require a flexible SAR processing scheme to account for nonlinear sensor trajectories during the synthetic aperture. In this contribution, a parallelized implementation of a time-domain back-projection SAR focusing algorithm based on NVIDIA's CUDA GPU computing framework is presented and discussed using a car-borne SAR data set. The processing performance is assessed using different hardware. In addition, a pre-processing scheme is described that allows for full 3-D motion compensation, yet staying conveniently in conventional slant-range/azimuth geometry of single-look complex SAR images.

Persistent scatterer interferometry relies on the assumption that only one dominant scatterer is present per range-azimuth resolution cell. If this criterion is not met the point target candidate is discarded during the iterative processing sequence. This one-scatterer assumption contrasts with the fact that in urban scenarios layover is an ubiquitous phenomenon, and, therefore two or even more scatterers per resolution cell occur frequently. SAR tomography has the potential to support persistent scatterer interferometry in urban areas by providing a means to identify and separate two scatterers in elevation direction. In this paper, we explore an interferometric stack consisting of 25 ENVISAT/ASAR SLC images over Bucharest using SAR tomography approaches combined with interferometric point target processing. Elevation profiles are extracted using beamforming and truncated singular value decomposition focusing approaches.

In this contribution, a car-borne SAR and InSAR experiment is described. The slope of a valley was imaged by means of a single-pass InSAR system mounted on a car driving on roads along the bottom of the valley. The GAMMA portable radar interferometer GPRI-II hardware with a modified antenna configuration was used for data acquisition. The experimental setup (1), SAR imagery focused along a slightly curved sensor trajectory (2), and first interferometric results (3) obtained using this configuration are presented.

Precise terrain-corrected georeferencing of synthetic aperture radar (SAR) images and derived products in range–Doppler coordinates is important with respect to several aspects, such as data interpretation, combination with other geodata products, and transformation of, e.g., terrain heights into SAR geometry as used in differential interferometric SAR (DInSAR) applications. For georeferencing, a lookup table is calculated and then refined based on a coregistration of the actual SAR image to a simulated SAR image. The impact of using two different implementations of such a simulator of topography-induced radar brightness, 1) an approach based on angular relationships and 2) a pixel-area-based method, is discussed in this letter. It is found that the pixel-area-based method leads to considerable improvements with regard to the robustness of georeferencing and also with regard to radiometric normalization in layover-affected areas.

In this contribution, tomographic imagery obtained from estimating the 3-D localization and the polarimetric signature of backscattering sources within a forest environment from fully-polarimetric multibaseline SAR data at L- and P-bands are presented. Both, polarization diversity and spatial diversity were exploited jointly within the tomographic focusing to estimate the targets' localization and polarimetric signature. We thereby extend our recently proposed time-domain back-projection (TDBP)-based tomographic focusing approach. The tomographic slices obtained from polarimetric spectral estimation using MLBF, Capon, and MUSIC are opposed to the results previously obtained by tomographic focusing of the individual polarization channels. The results are briefly discussed with respect to potential advancements towards more reliable estimation of forest parameters from SAR tomography data.

In this contribution Persistent Scatterer Interferometry (PSI) processings done in the framework of the FP7 Project PanGEO over a number of European sites are presented. After a short introduction of the PanGEO project, we present the data used, the processing done and the results of the PSI analysis. The influence of specifics as the presence of large non-urban areas, significant topography, seasonal effects, special deformation characteristics, and the size of the available data stacks on the processing are highlighted.

Forest canopies are semitransparent to microwaves at both L- and P-bands. Thus, a number of scattering sources and different types of scattering mechanisms may contribute to a single range cell of a synthetic aperture radar (SAR) image. By appropriately combining the SAR data of multiple parallel flight paths, a large 2-D aperture is synthesized, which allows for tomographic imaging of the 3-D structure of such semitransparent media and the underlying ground. A separate paper deals with the actual tomographic imaging part that leads to the 3-D data cube. In particular, three focusing techniques are described and analyzed: multilook beamforming, robust Capon beamforming, and multiple signal classification beamforming. In this paper, the resulting data products obtained by tomographically focusing two airborne multibaseline SAR data sets of a partially forested area, one at L-band and another at P-band, are subject to a detailed analysis with respect to the location and the type of backscattering sources. In particular, the following aspects are investigated: 1) The forest structure, as obtained from the vertical profiles of intensities at sample plot locations within the forest, is compared to the height distribution of the top of the forest canopy, as derived from airborne laser scanning data, and profiles are presented for all polarimetric channels and focusing techniques, as well as at both frequencies; 2) the type and location of scattering mechanisms are analyzed as functions of height for the two frequencies, namely, L- and P-bands, and using the polarimetric channels, as well as the Pauli and CloudePottier decompositions thereof; and 3) the accuracy of the ground elevation estimation obtained from the different focusing techniques and the two frequencies is assessed with the help of a lidar-derived digital elevation model.

In this paper, a time-domain back-projection based tomographic processing approach to a 3-D reconstruction grid is detailed, with the focusing in the third dimension being either modified versions of multilook standard beamforming, robust Capon beamforming, or multiple signal classification. The novel feature of the proposed approach compared to previous synthetic aperture radar (SAR) tomography approaches is that it allows for an approximation-free height-dependent calculation of the sample covariance matrix by exploiting the azimuth-focused data on the 3-D reconstruction grid. The method is applied to experimental multibaseline quad-pol SAR data at L- and P-bands acquired by German Aerospace Center's (DLR) E-SAR sensor: Tomographic images of a partially forested area, including a 3-D voxel plot that visualizes the very high level of detail of the tomographic image, are shown, and an analysis of the focusing performance is given for the full as well as reduced synthetic aperture in the normal direction.

In this paper, two fully-polarimetric tomographic SAR data sets of a forested area, at L-band and P-band, are analyzed with respect to the localization of scattering sources and scattering mechanisms. In particular, the 3D SAR data is examined regarding the performance of three different tomographic focusing techniques multilook standard beamforming, robust Capon beamforming, and MUSIC, as well as for both, the two frequency bands and the different polarimetric channels.

The propagation of spaceborne radar signals operating at L-band frequency or below can be seriously affected by the ionosphere. At high states of solar activity, Faraday rotation (FR) and signal path delays disturb radar polarimetry and reduce resolution in range and azimuth. While these effects are negligible at X-band, FR and the frequency-dependent path delays can become seriously problematic starting at L-band. For quality assurance and calibration purposes, existing L-band or potential spaceborne P-band missions require the estimation of the ionospheric state before or during the data take. This paper introduces two approaches for measuring the ionospheric total electron content (TEC) from single-polarized spaceborne SAR data. The two methods are demonstrated using simulations. Both methods leverage knowledge of the frequency-dependent path delay through the ionosphere: The first estimates TEC from the phase error of the filter mismatch, while the second gauges path-delay differences between up and down chirps. FR, mean (direct current) offsets, and noise contributions are also considered in the simulations. Finally, possibilities for further methodological improvements are discussed.

Standard focusing of data from synthetic aperture radar (SAR) assumes a straight recording track of the sensor platform. Small nonlinearities of airborne platform tracks are corrected for during a motion-compensation step while maintaining the assumption of a linear flight path. This paper describes the processing of SAR data acquired from nonlinear tracks, typical of sensors mounted on small aircraft or drones flying at low altitude. Such aircraft do not fly along straight tracks, but the trajectory depends on topography, influences of weather and wind, or the shape of areas of interest such as rivers or traffic routes. Two potential approaches for processing SAR data from such highly nonlinear flight tracks are proposed, namely, a patchwise frequency-domain processing and mosaicking technique and a time-domain back-projection-based technique. Both are evaluated with the help of experimental data featuring tracks with altitude changes, a double bend, a 90deg curve, and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared, impulse response functions of a point target are analyzed, and the coherence is evaluated. The experimental data were acquired by the German Aerospace Center's E-SAR L-band system.

Various tomographic processing methods have been investigated in recent years. The quality of the focused tomographic image is usually limited by several factors. In particular, Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. Neither time-domain back-projection (TDBP) processing, although providing a very accurate processing framework, is able to overcome the problem of ambiguous target detection in the tomographic image. In this paper, a possible extension of the TDBP approach to multi-looking based tomographic focusing methods like standard beamforming and Capon beamforming is discussed. Preliminary results obtained with a simulated and a real airborne tomographic P-band data set are shown.

Standard focusing of SAR data assumes a straight recording track of the sensor platform. Small non-linearities of airborne platform tracks are corrected for during a motion compensation step while keeping the assumption of a linear flight path. In the following, the processing of SAR data from non-linear tracks is discussed as may originate from small aircraft or drones flying at low altitude. They fly not a straight track but one dependent on topography, influences of weather and wind, or dependent on the shape of dedicated areas of interest such as rivers or traffic routes. A time-domain back-projection based technique, is proposed and evaluated with the help of experimental data featuring a drop in height, a double bend, a 90-degree curve and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared and the coherence is evaluated. The experimental data was acquired by the German Aerospace Center's E-SAR L-band system.

Recently, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated but the quality of the focused tomographic image is limited by several factors. In particular Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. We propose a tomographic focusing method based on the time-domain back-projection algorithm, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. We assess the tomographic focusing quality with the help of the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, preliminary results obtained with the newly acquired P-band tomographic data set consisting of eleven flight tracks are presented.