Matteo Nannini

Very-High-Resolution Airborne Synthetic Aperture Radar Imaging: Signal Processing and Applications

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Todays airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of todays very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions.

First Bistatic Spaceborne SAR Experiments With TanDEM-X

TanDEM-X (TerraSAR-X Add-on for Digital Elevation Measurements) is a high-resolution interferometric mission with the main goal of providing a global and unprecedentedly accurate digital elevation model of the Earth surface by means of single-pass X-band synthetic aperture radar (SAR) interferometry. Despite its usual quasi-monostatic configuration, TanDEM-X is the first genuinely bistatic SAR system in space. During its monostatic commissioning phase, the system has been mainly operated in pursuit monostatic mode. However, some pioneering bistatic SAR experiments with both satellites commanded in nonnominal modes have been conducted with the main purpose of validating the performance of both space and ground segments in very demanding scenarios. In particular, this letter reports about the first bistatic acquisition and the first single-pass interferometric (mono-/bistatic) acquisition with TanDEM-X, addressing their innovative aspects and focusing on the analysis of the experimental results. Even in the absence of essential synchronization and calibration information, bistatic images and interferograms with similar quality to pursuit monostatic have been obtained.

Estimation of the Minimum Number of Tracks for SAR Tomography

Synthetic aperture radar tomography (SARTom) is the natural extension of SAR interferometry to solve for multiple phase centers within a resolution cell and obtain the 3-D representation of a scene. This paper deals with the determination of the minimum number of tracks required to perform SARTom. Through the prolate spheroidal wave functions, the number of equivalent targets of a volumetric source is derived, and from it, the minimum number of observations required to apply subspace superresolution methods is computed. The minimum tomographic aperture length is also investigated. The results are validated on real data acquired in L-band by the experimental SAR system of the German Aerospace Center.

Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas

Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a stack of multibaseline measurements. In addition, recent work has addressed the tomographic inversion under the framework of compressed sensing, thereby recovering sparse cross-range profiles from a reduced set of measurements. This paper differs from previous publications, in that it focuses on sparse expansions in the wavelet domain while working with the second-order statistics of the corresponding multibaseline measurements. In this regard, we elaborate on the conditions under which this perspective is applicable to forested areas and discuss the possibility of optimizing the acquisition geometry. Finally, we compare this approach with traditional nonparametric ones and validate it by using fully polarimetric L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR).

First 3-D Reconstructions of Targets Hidden Beneath Foliage by Means of Polarimetric SAR Tomography

SAR tomography (SARTom) is an imaging technique that allows multiple phase center separation in the vertical direction, leading to a 3-D reconstruction of the imaged scene. The retrieval of volume structure information (e.g., for forest classification) and the solution of the layover problem are two of the most promising applications. In this letter, SARTom, in combination with polarimetry (PolSARTom), is exploited to image and to extract characteristic features (e.g., shape and height) of targets hidden beneath foliage. This analysis is applied to L-band airborne data acquired by the E-SAR system of the German Aerospace Center (DLR) during a tomographic campaign that took place in September 2006 on the test site of Dornstetten (Germany).

Multisignal Compressed Sensing for Polarimetric SAR Tomography

In recent years, 3-D imaging by means of polarimetric synthetic aperture radar (SAR) sensors has become a field of intensive research. In SAR tomography, the vertical reflectivity function for every azimuth-range pixel is usually recovered by processing data collected using a defined repeat-pass acquisition geometry. The most common approach is to generate a synthetic aperture in the elevation direction through imaging from a large number of parallel tracks. This imaging technique is appealing, since it is very simple. However, it has the drawback that large temporal baselines can severely affect the reconstruction. In an attempt to reduce the number of parallel tracks, we propose a new approach that exploits structural correlations between neighboring azimuth-range pixels and/or polarimetric channels. As a matter of fact, this can be done under the framework of distributed compressed sensing (CS) (DCS), which stems from CS theory, thus also exploiting sparsity in the tomographic signal. Finally, results demonstrating the potential of the DCS methodology will be validated by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).

A Data-Adaptive Compressed Sensing Approach to Polarimetric SAR Tomography of Forested Areas

Super-resolution imaging via compressed sensing (CS)-based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography. In the case of partial scatterers, the mainstream has so far been twofold, in that the tomographic reconstruction is conducted by either directly working with multiple looks and/or polarimetric channels or by exploiting the corresponding single-channel second-order statistics. In this letter, we unify these two methodologies in the context of covariance fitting. In essence, we exploit the fact that both vertical structures and the unknown polarimetric signatures can be approximated in a low-dimensional subspace. For this purpose, we make use of a wavelet basis in order to sparsely represent vertical structures. Additionally, we synthesize a data-adaptive orthonormal basis that spans the space of polarimetric signatures. Finally, we validate this approach by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).

Multi-signal compressed sensing for polarimetric SAR tomography

In recent years, three-dimensional imaging by means of SAR tomography has become a field of intensive research. In SAR tomography, the vertical reflectivity function for every azimuth-range pixel is usually recovered by processing data collected using a defined repeat pass acquisition geometry. The most common approach is to generate a synthetic aperture in the elevation direction through imaging from a large number of parallel tracks. This imaging technique is appealing, since it is very simple. However, it has the drawback that large temporal baselines, which is the case for space-borne platforms, can severely affect the reconstruction. In an attempt to reduce the number of parallel tracks, we propose a new tomographic focusing approach that trades number of SAR images for correlations between neighboring azimuth-range pixels and polarimetric channels. As a matter of fact, this can be done under the framework of Distributed Compressed Sensing (DCS), which stems from Compressed Sensing (CS) theory, thus also exploiting sparsity in our tomographic signal. In addition, we address the problem of measurements affected by additive as well as multiplicative speckle noise. Results demonstrating the potential of the DCS methodology will be validated by using fully polarimetric L-band data acquired by the E-SAR sensor of DLR.

Tomographic 3D reconstruction from airborne circular SAR

The study of data acquired over a circular trajectory has raised an increasing interest in the SAR community. Two main reasons summarize the interest in such geometry. First, sub-wavelength resolution can be achieved, as the targets in the spotted area are observed under a 360º aperture. Second, the use of the information from different azimuthal directions allows one to obtain information of the scene in the third dimension, making possible a 3D target reconstruction. In any case, both applications require certain target reflectivity homogeneity. This paper shows several processing results and analyzes the potentials and limitations of circular SAR to perform tomography of semi-transparent media. Special processing aspects, like the estimation of residual motion errors due to inaccuracies in the navigation data, are also addressed. Data acquired at L-band by DLRs E-SAR system are used to demonstrate the high resolution and tomographic imaging capabilities of circular SAR. The results include the tomogram of a Luneburg lens, as well as preliminary results over man-made targets and vegetation.

Target separation in SAR image with the MUSIC algorithm

The aim of this work is to exploit the MUSIC algorithm performance in order to enhance target separability in range and azimuth, i.e. achieve point targets separation inside a resolution cell. Simulations have been done in order to plan and check the feasibility of a super-resolution experiment that took place in September 2006 on the test site of Oberpfaffenhofen (Germany). The data set has been acquired with the E-SAR system of the DLR in X-band. The targets to be separated were seven small corner reflectors that have been placed in a way that their response falls in one or, at maximum, two resolution cells of the standard Fourier SAR image. A post-processing implementation of the MUSIC algorithm has been proposed allowing, in the already focused SAR image, to retrieve the targets geometry. Conditions and analysis of the results have been carried out.