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Multidimensional synthetic aperture radar (SAR) imaging is a technique based on coherent SAR data combination for space (full 3-D) and space deformation--velocity (4-D) analysis. It is an extension of the concepts of SAR interferometry and differential interferometry SAR and offers new options for the analysis and monitoring of ground scenes. In this paper, we consider the problem of detecting single scatterers for localization and monitoring issues. To this end, we resort to a constant false alarm rate (CFAR) detection scheme which can be synthesized according to three different design criteria: generalized likelihood ratio test, Rao test, and Wald test. At the analysis stage, the performance of the aforementioned detector is compared to that of a previously proposed CFAR scheme, based on the multi-interferogram complex coherence and widely used in persistent scatterer interferometry. The analysis is conducted both on simulated and on real SAR data, acquired by ERS-1/2 satellites. Finally, Cramer--Rao lower bounds for the estimation of the scatterer elevation and velocity are provided. Index Terms--Differential tomography, multidimensional synthetic aperture radar (SAR) imaging, scatterer detection.

The superposition of contributions from different stable targets within the same pixel is a phenomenon that may impair the imaging and monitoring of ground scatterers via the multipass synthetic aperture radar (SAR) interferometry technique. Three-dimensional SAR imaging, also known as SAR tomography, uses multiple views to profile the scattering power at different heights. This technique has been shown to be capable of separating interfering target responses on real data. Differential SAR tomography has been recently proposed as a technique that extends the potentialities of SAR tomography to the target deformation monitoring. It performs a 4-D space--velocity imaging that enables not only separating interfering targets in elevation but also distinguishing their single slow deformation velocities. This work addresses for the first time the application of 4-D SAR imaging to real data to determine the height and mean deformation velocity of single scatterers and double-scattering mechanisms interfering at high resolution in the same pixel. It also discusses the postprocessing steps required to identify the presence of stable single and double scatterers after elevation--velocity focusing. Moreover, it proposes a technique for the extraction of time series from interfering targets to measure possible nonlinear temporal deformations. Index Terms--Differential synthetic aperture radar (SAR) tomography, multibaseline/multitemporal coherent SAR processing, permanent scatterers interferometry, 4-D SAR imaging.

Three-dimensional synthetic aperture radar (SAR) imaging, a technique also known as SAR tomography, uses multiple views to extend the capability of SAR systems to 3-D imaging by achieving a profiling of the scattering power at different heights. Multiple views are obtained with the current satellite technology via successive passes of a single antenna SAR sensor over the same scene, but next-generation sensor formations are foreseen to acquire multistatic data. Conventional processing, such as the beamforming, or singular values decomposition inversion is based on geometrical derivations and, hence, assumes the accurate phase calibration and the absence of target decorrelation. This paper analyzes the effects of phase miscalibration due to residual uncompensated atmospheric contribution and temporal decorrelation and proposes a 3-D imaging technique based on a linear minimum mean square error approach. The resulting algorithm extends the possibilities of the conventional processing by carrying out an integration of data that accounts for the a priori data correlation properties. Hence, it allows handling of the presence of additional stochastic contributions such as: temporal coherence losses and atmospheric phase miscalibration. Moreover, with reference to future bistatic and multistatic systems, it permits an improved coherent integration of data acquired by simultaneous antenna in repeated passes. Index Terms--3-D SAR tomography, 3-D synthetic aperture radar (3-D SAR) imaging.

Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique that allows monitoring ground deformation with accuracy of the order of fractions of the radiated wavelength, by means of proper combination and processing of repeat-pass data. In contrast to the satellite case, application of such a technique to airborne data is not, today, a well-established task. Several airborne campaigns, involving mainly C/L-band data, have been planned in the last years to exploit the potentialities of these more flexible platforms for deformation monitoring. In this paper, we show the results of an airborne DInSAR X-band experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system. We discuss the processing chain applied to the acquired data, which allows achieving a satisfactory compromise between accuracy and efficiency. Eleven repeated passes were carried out in two days; two corner reflectors were located on the ground in a hilly region. One corner reflector was vertically moved between the two days to evaluate the system detection capability. Moreover, we carry out an analysis of all possible differential interferograms for a region 2 x 4 km wide. Index Terms--Airborne differential SAR interferometry, airborne repeat pass SAR interferometry, synthetic aperture radar (SAR).

Microwave scattering is a rather complex mechanism, especially in urban areas. Three-dimensional (3-D) synthetic aperture radar (SAR) tomography is a technique that uses multiple views to map the scattering power at different heights, thus extending the capability of SAR sensors to fully image the scene in the 3-D space. This paper presents a first validation of spaceborne long-term SAR tomography by demonstrating the capability to resolve a simple layover case, i.e., to separate single- and double-scattering mechanisms within imaged pixels. Results obtained with real data acquired by the European Remote Sensing 1 and 2 (ERS-1 and ERS-2) satellites over the urban area of Napoli are presented. As an additional contribution, an innovative algorithm estimating residual topography and surface deformation, called the spatial-differencing technique, is also discussed in detail at the data calibration stage. Index Terms--Multibaseline coherent synthetic aperture radar (SAR) processing, SAR tomography, three-dimensional (3-D) SAR focusing.

Accurate subpixel registration of synthetic aperture radar (SAR) images is an issue that is again growing interest since its initial developments related to two-pass interferometry. Recent progress in coherent (multichannel) SAR processing raises the need for accurate registration of data takes acquired with large baseline spans, high temporal coverage, and with different frequency and/or operational modes. In this paper, we discuss a SAR image-registration procedure, based on the use of external measures which allows obtaining a very accurate alignment of SAR images. The presented technique makes use of a digital elevation model and of the precise information about the acquisition flight tracks, to compute the warping functions that map the position of each pixel in the different takes, thus avoiding any approximation. The resulting algorithm is simple, robust, precise, and very efficient; as a matter of fact, it may achieve high accuracy even in critical areas, such as steep topography regions. Moreover, the availability of an analytical and exact model allows performing a detailed sensitivity analysis that can be useful in evaluating the applicability of this technique even to future high-precision satellite systems. Extensive testing, carried out on several real European Remote Sensing and ENVISAT datasets, clearly shows the effectiveness of such algorithm in registering critical SAR images. Index Terms--Image registration, multichannel SAR, synthetic aperture radar (SAR) interferometry (InSAR).

Synthetic aperture radar (SAR) interferometry is a modern efficient technique that allows reconstructing the height profile of the observed scene. However, apart for the presence of critical nonlinear inversion steps, particularly crucial in abrupt topography scenarios, it does not allow one to separate different scattering mechanisms in the elevation (height) direction within the ground pixel. Overlay of scattering at different elevations in the same azimuth-range resolution cell can be due either to the penetration of the radiation below the surface or to perspective ambiguities caused by the side-looking geometry. Multibaseline three-dimensional (3-D) SAR focusing allows overcoming such a limitation and has thus raised great interest in the recent research. First results with real data have been only obtained in the laboratory and with airborne systems, or with limited time-span and spatial-coverage spaceborne data. This work presents a novel approach for the tomographic processing of European Remote Sensing satellite (ERS) real data for extended scenes and long time span. Besides facing problems common to the airborne case, such as the nonuniformly spaced passes, this processing requires tackling additional difficulties specific to the spaceborne case, in particular a space-varying phase calibration of the data due to atmospheric variations and possible scene deformations occurring for years-long temporal spans. First results are presented that confirm the capability of ERS multipass tomography to resolve multiple targets within the same azimuth-range cell and to map the 3-D scattering properties of the illuminated scene. Index Terms--Multibaseline, multipass, synthetic aperture radar (SAR), three-dimensional (3-D) focusing, tomography.

This 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. Index Terms--Synthetic aperture radar (SAR), three-dimensional focusing, tomography.

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. Index Terms--Ground deformations, SAR interferometry, synthetic aperture radar (SAR).

This paper addresses the problem of filtering interferometric synthetic aperture radar (IFSAR) signals in presence of nonplanar 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 (MMSE), filtering procedure. The algorithm is flexible and, beside the standard stripmap-stripmap interferometry, it may be applied to IFSAR 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 (DEM) 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. Index Terms--Minimum mean square error (MMSE) interferometric filtering, SAR interferometry (IFSAR), synthetic aperture radar (SAR).

This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to 'some' known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures.

Efficient and precise compensation of the range cell migration (RCM) effect is a key point for a fast and accurate Synthetic Aperture Radar (SAR) data processor. In particular the range-dependent nature of the range cell migration effect complicates the compensation operation. It has been recently shown that an exact compensation of the range-dependent RCM (RDRCM) phenomenon can be carried out either by applying the chirp scaling algorithm or the chirp z-transform procedure. This paper investigates the relationship between the two methods. In particular, it is shown that the chirp z-transform based approach represents a particular implementation of the chirp scaling algorithm. A final discussion is dedicated to show how the chirp z-transform and the chirp scaling procedure can be applied within a SAR data processing algorithm. Index Terms - Synthetic aperture radar processing.

This paper is concerned about the generation of interferometric phase patterns using Synthetic Aperture Radar (SAR) images obtained by processing raw data and reference function both quanfized at one bit (Signum Coded). Such processing technique involves one-bit coded (i.e., binary) sequences, and can be efficiently implemented in real time using very simple and low cost hardware. It is shown that the proposed SC processing technique preserves, besides the image intensities, also interferometric phase patterns, before and after phase unwrapping. To test the performance of the proposed technique, experiments have been carried out on real data relative to the ERS-1 mission. Quantitative comparison between the results of conventional and SC processing clearly show that the presented method can be used for quick-look DEM's generation. Moreover, in accordance with the SC-SAR theory, an upsampling has also been performed on the signals to be processed to obtain higher quality patterns. This produce a noticeable improvement of the obtained results, so that the SC techniques can be considered a valid alternative to the conventional ones, still preserving the advantages in terms of real time. Index Terms - Synthetic aperture radar (SAR), SAR interferometry, SC-SAR.

In this paper, we exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. We present a solution to improve the unwrapping performance of the C- and X-band data by considering the L-band unwrapped pattern. A new algorithm for the generation of a single digital elevation model (DEM) combining L-, C-, and X-band information is presented. This solution is based on the fusion of the unwrapped phase patterns by using a Kalman filter. The proposed fusion operation also accounts for the coherence characteristics of the three data sets. The selected test site is the Mt. Etna region in Italy which is very interesting from the volcanological and geological point of view. Numerical assessments of the achieved results are provided by evaluating the height accuracy with respect to a reference DEM.

Any method that permits retrieving full range (unwrapped) phase values starting from their (-[Pi], [Pi]) determination (wrapped phase) can be defined as a phase unwrapping technique. This paper addresses a new procedure for phase unwrapping especially designed for Interferometric synthetic aperture radar applications. The proposed algorithm is based on use of Green's first identity. Results on simulated as well as on real data are presented. They both confirm the excellent performance of the procedure.

We 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 of the proposed algorithm 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 us to perform a bulk azimuth raw data compression and to achieve 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. Index Terms--Raw data focusing, spectral analysis (SPECAN) processing algorithms.