The reliability of any final differential synthetic aperture radar (SAR) interferometry (DInSAR) product is directly related to the phase quality of the interferograms involved in the processing. Performing an appropriate selection of high-quality pixels is hence mandatory in order to avoid the inclusion of noisy data in the processing and thus obtain reliable deformation information within the area of study. In this framework, a new full-resolution pixel selection method based on exploiting the spectral properties of pointlike scatterers is presented. The method is developed from the concept of the so-called coherent scatterers, which are characterized by having a correlated spectrum in a single acquisition, but now involving the temporal axis in the detection. Using the spectral properties of scatterers to perform the DInSAR pixel selection step presents some advantages with respect to the well-known permanent scatterer (PS) approach. On the one hand, the radiometric calibration of data is not required since the detection is now not dependent on the amplitude behavior of scatterers. On the other hand, a reliable pixel selection can be performed even with a reduced number of images due to the nature of the estimator. In contrast, its main limitation relies on the loss of range resolution involved in the sublook generation process. The method is more suited for urban scenarios where the density of temporally stable pointlike scatterers is generally higher. In this context, the final deformation maps obtained using the new method presented are compared, in terms of density and phase quality, with the ones obtained with the well-known traditional PS approach, showing a similar performance. Finally, since both methods characterize pointlike scatterers from different points of view, the combination of both techniques is proposed leading to a significant increase in the pixels' density and giving place to a meaningful improvement in the final DInSAR results.

In this paper, bistatic interferometry using fixed-receiver configurations is addressed both theoretically and experimentally. The analytical expressions for interferometric phase and height sensitivity are derived, and a full interferometric processing chain for digital elevation model (DEM) generation is presented. The derived expressions are general, and they can be applied to two possible acquisition geometries: backscattering and forward scattering. The theoretical developments are complemented with experimental results done with the bistatic receiver Synthetic Aperture radar Bistatic Receiver for INterferometric Applications. The obtained DEMs are compared with a DEM from the Shuttle Radar Topography Mission and a digital terrain model from the Institut Cartografic de Catalunya. The comparison allows one to validate the results and demonstrate to which particular features of the scene that the bistatic radar is sensitive.

This paper discusses the use of Capon's minimum-variance method (MVM) and Amplitude and Phase EStimation (APES) spectral-estimation algorithms to synthetic aperture radar rangeazimuth focusing. The rationale of the algorithms is discussed. An implementation of a Capon or APES processing chain is explained, and processing parameters such as chip-image size, resampling factor, and diagonal loading are discussed. For multichannel cases, a joint-processing approach is presented. A set of Monte Carlo simulations are described and used to benchmark Capon- and APES-based processing against conventional matched-filter-based approaches. Both methods improve the resolution and reduce sidelobes. APES yields generally better estimates of amplitude and phase than Capon but with worse resolution. Results with RADARSAT-2 quad-polarization data over Barcelona are used to qualitatively study the real-life performance of these algorithms.

Radar data have already proven to be compressible with no significant losses for most of the applications in which it is used. In the framework of information theory, the compressibility of a signal implies that it can be decomposed onto a reduced set of basic elements. Since the same quantity of information is carried by the original signal and its decomposition, it can be deduced that a certain degree of redundancy exists in the explicit representation. According to the theory of compressive sensing (CS), due to this redundancy, it is possible to infer an accurate representation of an unknown compressible signal through a highly incomplete set of measurements. Based on this assumption, this paper proposes a novel method for the focusing of raw data in the framework of radar imaging. The technique presented is introduced as an alternative option to the traditional matched filtering, and it suggests that the new modes of acquisition of data are more efficient in orbital configurations. In this paper, this method is first tested on 1-D simulated signals, and results are discussed. An experiment with synthetic aperture radar (SAR) raw data is also described. Its purpose is to show the potential of CS applied to SAR systems. In particular, we show that an image can be reconstructed, without the loss of resolution, after dropping a large percentage of the received pulses, which would allow the implementation of wide-swath modes without reducing the azimuth resolution.

This paper presents across-track tomography applied to a bistatic geometry with fixed receivers. This kind of geometry can overcome some of the classical monostatic tomography limitations such as temporal decorrelation and irregular baseline distribution. The Remote Sensing Laboratory (RSLab) of the Universitat Politècnica de Catalunya (UPC) has implemented a SAR Bistatic Receiver for INterferometric Applications, SABRINA, with 4-channels. SABRINA has been used to carry out a bistatic tomographic experiment. The acquired data has been processed with different tomographic methods and their performances compared.

This paper gives a quick overview of inversion methods for bistatic tomographic processing. The methods are tested over simulated and real data. The real data has been acquired from a set of indoor experiments carried out in the Radiation Laboratory (RadLab), at the University of Michigan. A scale model with a house, some trees and a rough surface on the ground has been built to reproduce an urban scenario.

This paper discusses temporal and phase synchronization in bistatic synthetic aperture radar (SAR) systems that use orbital sensors as coherent sources of opportunity and receivers at a fixed location. The discussion is particularized to SAR Bistatic Receiver for INterferometric Applications (SABRINA), a ground-based bistatic receiver that uses ENVISAT and ERS-2 as transmitters. Transmitter-receiver synchronization is hindered by the presence of independent reference oscillators at the transmit and receive end and by the lack of a common time frame. Phase synchronization and pulse alignment are achieved using a dedicated channel that receives a clean signal directly from the satellite. How to align the acquired data with the satellite orbit and how to estimate the Doppler centroid (DC) are studied. It is shown that in the bistatic configuration considered, the receiver provides an implicit control point which limits the negative impact of a DC misestimation on the resulting images. An algorithm to achieve this temporal alignment using the apparent phase history of the received pulses is proposed. Finally, this algorithm is validated through Monte Carlo simulations and experimental data acquired by SABRINA.

This letter discusses the implementation of SABRINA, Synthetic Aperture radar Bistatic Receiver for Interferometric Applications. The ground resolution of a fixed-receiver bistatic system is studied, showing that it is comparable to that of a monostatic system. Due to the short distance from target to receiver, large sensitivity is obtained. The noncooperative nature of the bistatic system forces a conservative data-acquisition strategy based on continuously sampling the scattered signal during a temporal window around the predicted satellite overpass time. Also, to be able to synchronize the system in time and in frequency, sampling of a direct signal obtained through an antenna pointed at the satellite is required. Besides the signal processing required to phase-lock the received signal, the bistatic synthetic aperture radar processing needs to take into account the azimuth-dependent phase history. First focused images obtained with the SABRINA-ENVISAT combination are discussed.