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The Scientific World Journal
Volume 2015, Article ID 949807, 6 pages
http://dx.doi.org/10.1155/2015/949807
Research Article

Support Detection for SAR Tomographic Reconstructions from Compressive Measurements

Dipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope”, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, Italy

Received 10 April 2015; Revised 4 August 2015; Accepted 5 August 2015

Academic Editor: Alvaro Rocha

Copyright © 2015 Alessandra Budillon and Gilda Schirinzi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The problem of detecting and locating multiple scatterers in multibaseline Synthetic Aperture Radar (SAR) tomography, starting from compressive measurements and applying support detection techniques, is addressed. Different approaches based on the detection of the support set of the unknown sparse vector, that is, of the position of the nonzero elements in the unknown sparse vector, are analyzed. Support detection techniques have already proved to allow a reduction in the number of measurements required for obtaining a reliable solution. In this paper, a support detection method, based on a Generalized Likelihood Ratio Test (Sup-GLRT), is proposed and compared with the SequOMP method, in terms of probability of detection achievable with a given probability of false alarm and for different numbers of measurements.