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Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, Autofocusing, Moving Targets, and Compressed Sensing
Authors: Müjdat Çetin, Ivana Stojanovic, N. Ozben Onhon, Kush R. Varshney, Sadegh Samadi, W. Clem Karl, and Alan S. Willsky
Published in: IEEE Signal Processing Magazine, vol. 31, no. 4, pp. 27-40, July 2014
Publication year: 2014
Abstract: This article presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imag-ing. In particular, it reviews 1) the analysis and synthe-sis-based sparse signal representation formulations for SAR image for-mation together with the associated im-aging results, 2) sparsity-based methods for wide-angle SAR im-aging and anisotropy charac-terization, 3) sparsity-based methods for joint imaging and autofocusing from data with phase errors, 4) techniques for exploit-ing sparsity for SAR imag-ing of scenes containing moving objects, and 5) re-cent work on compressed sensing (CS)-based analysis and design of SAR sensing missions.
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