Sparsity-driven synthetic aperture radar imaging [Reconstruction, autofocusing, moving targets, and compressed sensing]

摘要

This article presents a survey of recent research on\udsparsity-driven synthetic aperture radar (SAR) imaging.\udIn particular, it reviews 1) the analysis and synthesis-\udbased sparse signal representation\udformulations for SAR image formation\udtogether with the associated imaging\udresults, 2) sparsity-based\udmethods for wide-angle SAR imaging\udand anisotropy characterization,\ud3) sparsity-based\udmethods for joint imaging\udand autofocusing from\uddata with phase errors,\ud4) techniques for exploiting\udsparsity for SAR imaging\udof scenes containing\udmoving objects, and 5) recent\udwork on compressed\udsensing (CS)-based analysis and\uddesign of SAR sensing missions.