Abstract
With the increase of the imaging resolution, the resulting enormous amount of sampling raw data aggravates transmission and storage load for multi-channel synthetic aperture radar (SAR) system. Considering the fact that the correlation among the dual-channel SAR images is high, we propose a Bayesian compressive sensing (BCS) based SAR imaging algorithm for ground moving targets indication (GMTI) system, which uses Laplace priors on the basis coefficients in a hierarchical manner. The simulation results show that the proposed algorithm can successfully detect the moving target and meanwhile suppress the static clutter scattering centers, with 50% sampling data of those required by the range-Doppler(RD) algorithm.
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