Synthetic aperture radar (SAR) data are affected by speckle noise, originated by the SAR system's coherent nature. The problem of speckle noise in one-dimensional (1-D) data is already solved, as speckle has a multiplicative characteristic. SAR polarimetry represents an extension to multidimensional data by the use of polarization wave diversity. As a consequence of the existence of a correlation degree between the SAR images, the 1-D speckle noise model cannot be extended to multidimensional SAR data. This paper is devoted to present a completely new speckle noise model for the complex covariance matrix describing polarimetric SAR data in the distributed scatterers case. As is shown, this new model is able to identify which are the noise mechanisms in all the covariance matrix elements. The speckle noise model is validated by using real L-band polarimetric data acquired with the German E-SAR sensor.

This paper addresses the problem of interferometric phase noise reduction in synthetic aperture radar interferometry. A new phase noise model in the complex domain is introduced and validated by using both simulated and real interferograms. This noise model is also derived in the complex wavelet domain, where a novel noise reduction algorithm, which is not based on a windowing process and without the necessity of phase unwrapping, is addressed. The use of the wavelet transform allows to maintain the spatial resolution in the filtered phase image and prevents to filter low coherence areas. By using both, simulated as well as real interferometric phase images, the performance of this algorithm, in terms of noise reduction, spatial resolution maintenance, and computational efficiency, is reported and compared with other conventional filtering approaches.

In this paper, a new model-based technique for the compensation of severe height-dependent atmospheric artifacts, using ground-based synthetic aperture radar (SAR) data over mountainous regions, is proposed. The method presented represents an extension of already existing techniques, but now taking into account the effect of steep topography in the atmospheric phase screen compensation process. In addition, the technique is adapted to work with polarimetric SAR data, showing, in that case, a noticeable improvement in the compensation process. The method is validated in the mountainous environment of El Forn de Canillo, located in the Andorran Pyrenees, where there is a slow-moving landslide that nowadays is being reactivated coinciding with strong rain episodes. In this framework, ten zero-baseline fully polarimetric data sets have been acquired at X-band during a one-year measurement campaign (October 2010-October 2011) with the GB-SAR sensor developed at the Universitat Politècnica de Catalunya. First, the impact of the severe atmospheric fluctuations among multitemporal GB-SAR measurements is carefully studied and analyzed. Hence, the need to correctly estimate and compensate the resulting phase differences when retrieving interferometric information is put forward in the frame of differential-SAR-interferometry applications.

In this letter, a coherence-based technique for atmospheric artifact removal in ground-based (GB) zero-baseline synthetic aperture radar (SAR) acquisitions is proposed. For this purpose, polarimetric measurements acquired using the GB-SAR sensor developed at the Universitat Politecnica de Catalunya are employed. The heterogeneous environment of Collserola Park in the outskirts of Barcelona, Spain, was selected as the test area. Data sets were acquired at X-band during one week in June 2005. The effects of the atmosphere variations between successive zero-baseline SAR polarimetric acquisitions are treated here in detail. The need to compensate for the resulting phase-difference errors when retrieving interferometric information is put forward. A compensation technique is then proposed and evaluated using the control points placed inside the observed scene.

The Remote Sensing Laboratory of the Universitat Politecnica de Catalunya carried out a one-year measuring campaign in the village of Sallent, northeastern Spain, using a polarimetric ground-based synthetic aperture radar (SAR) sensor. The objective was to study the subsidence phenomenon induced by the salt mining activity conducted in this area up to the middle of the last century. Zero-Baseline polarimetric SAR (PolSAR) data were gathered at X-band in nine different days, from June 2006 to March 2007. In this letter, the problem of extracting subsidence information from fully PolSAR acquisitions for the retrieval of high-quality deformation maps is addressed. After compensating for the atmospheric artifacts caused by troposphere changes, the linear component of the deformation process is estimated separately for each polarization channel with the Coherent Pixels Technique (CPT). Afterward, a novel polarimetric approach mixing the differential-phase information of each polarization channel is proposed. The results obtained in the two cases are quantitatively compared, and the advantages provided by the polarimetric acquisitions are finally stressed.

In this paper, the capability of ultra-wide-band (UWB) sensor arrays for tomographic radar of electrically large objects is presented. The major concern when imaging is extended to real objects is to achieve a correct reconstruction of the object shape and its electric properties. A general framework based on a UWB bifocusing operator (UWB-BF) with good tomographic imaging capabilities is presented. This general approach provides a comprehensive understanding of the basic tradeoffs with regard to sensing geometry and image quality parameters. Through numerical simulations and measurements applied to canonical as well as to complex objects, basic design criteria are assessed and the potential of UWB tomographic radar imaging is presented.