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The paper deals with the use of multipass synthetic aperture radar (SAR) data in order to achieve three-dimensional tomography reconstruction in presence of volumetric scattering. Starting from azimuth- and range-focused SAR data relative to the same area, neglecting any mutual interaction between the targets, and assuming the propagation in homogeneous media, we investigate the possibility to focus the data also in the elevation direction. The problem is formulated in the framework of linear inverse problem and the solution makes use of the singular value decomposition of the relevant operator. This allows us to properly take into account nonuniform orbit separation and to exploit a priori knowledge regarding the size of the volume interested by the scattering mechanism, thus leading to superresolution in the elevation direction. Results obtained on simulated data demonstrate the feasibility of the proposed processing technique.

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

This paper addresses the problem of filtering Interferometric Synthetic Aperture Radar signals both in presence of non-planar topography to mitigate geometrical decorrelation effects. The problem is space-variant; we assume knowledge about the scene topography and derive an optimal, Minimum Mean Square Error, filtering procedure. The algorithm is flexible and, beside the standard stripmap-stripmap interferometry, it may be applied to interferometric SAR data acquired in any operative mode: for instance in scan-scan, scan-strip and scan-spot interferometry. The scene topography contribution may be either derived from an external rough Digital Elevation Model or directly estimated from the SAR data. The filtering technique is extended to the azimuth direction to account for possible Doppler Centroid decorrelation. Experimental results carried out on real data confirm the validity of the theory and show that this filtering procedure allows us to obtain a reduction of the interferometric noise content. Its gain is particularly marked in the cases of steep topography, where application of the standard common band filters could deteriorate the signal quality, or for large Doppler Centroid shifts between the two acquisitions.

Synthetic aperture radar (SAR) systems require that a focusing operation be performed on the received backscattered echoes (raw data) to generate high-resolution microwave images. Either due to platform attitude instabilities, or to Earth rotation effects, the SAR raw data may be acquired in "squinted" geometries, i.e., with the radar beam directed with an offset angle (squint angle) from the broadside direction. This research investigates the impact of the focusing operation carried out on squinted raw data acquisitions performed by SAR sensors operating in the stripmap mode. To this end the 2D frequency SAR processing approach is generalized with respect to conical, i.e., nonorthogonal, reference systems. This allows analysis of the geometric, spectral, and phase aberrations introduced in the images by the chosen processing geometry with respect to the acquisition, and identification of the focusing procedure that minimizes these aberrations. The whole theory is validated by experimental results carried out on simulated data. Moreover, the extension of this analysis to the interferometric case where these aberrations may have a significant role is also investigated.

The authors present a new spotlight SAR data-focusing algorithm based on a two-step processing strategy that combines the advantages of two commonly adopted processing approaches: the efficiency of SPECAN algorithms and the precision of stripmap focusing techniques. The first step implements a linear and space-invariant azimuth filtering that is carried out via a deramping-based technique representing a simplified version of the SPECAN approach. This operation allows performing a bulk azimuth raw data compression and achieving a pixel spacing smaller than (or equal to) the expected azimuth resolution of the fully focused image. Thus, the azimuth spectral folding phenomenon, typically affecting the spotlight data, is overcome, and the space-variant characteristics of the stripmap system transfer function are preserved. Accordingly, the residual and precise focusing of the SAR data is achieved by applying a conventional stripmap processing procedure requiring a minor modification and implemented in the frequency domain. The extension of the proposed technique to the case of high bandwidth transmitted chirp signals is also discussed. Experiments carried out on real and simulated data confirm the validity of the presented approach, which is mainly focused on spaceborne systems

We investigate the possibility to generate a large-scale Digital Elevation Model by applying the Synthetic Aperture Radar interferometry technique and using tandem data, acquired by the ERS-1/ERS-2 sensors. The presented study is mainly focused on the phase unwrapping step that represents the most critical point of the overall processing chain. In particular, rye concentrate on the unwrapping problems related to the use of a large ERS tandem data set that, in order to be unwrapped, must be partitioned. The paper discusses the inclusion of external information (even rough) of the scene topography, the application of a region growing unwrapping technique and the insertion of possible constraints on the phase to be retrieved in order to minimize the global unwrapping errors. Our goal is the generation of a digital elevation model relative to an area of 300 km by 100 km located in the southern part of Italy. Comparisons between the achieved result and a precise digital terrain model, relative to a smaller area, are also included.