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In this paper, we investigate ground moving target imaging (GMTIm) by synthetic aperture radar (SAR) under sparse Bayesian learning (SBL) framework. To automatically determine the parametric dictionary used in the framework, an novel time-frequency representation method, known as Lv's distribution (LVD), is adopted, which is superior to represent multiple moving targets on the Doppler centroid frequency...
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