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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 90 circ 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.

First results using the new Sentinel-1 SAR look very promising but the special interferometric wideswath data acquired in the TOPS mode makes InSAR processing challenging. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful "book-keeping" in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR and PSI work.

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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.Index Terms-Deformation analysis in urban areas, persistent scatterer interferometry (PSI), synthetic aperture radar (SAR) tomography.

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.

Abstract-Differential interferometry using groundbased 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 pre-processing 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 SLC 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 pre-processing 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.

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. ANALYZING TOMOGRAPHIC SAR DATA OF A FOREST WITH RESPECT TO FREQUENCY, POLARIZATION, AND FOCUSING TECHNIQUE Othmar Frey and Erich MeierRemote Sensing Laboratories University of Zurich, Switzerland ABSTRACTIn 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.