Sparse passive radar imaging based on DVB-S using the Laplace-SLIM algorithm

This paper studies sparse image reconstruction based on digital video broadcasting-satellites (DVB-S) system. The signal model is slightly different from our previous research [1-2], i.e. we consider the Swerling I model to characterize the target response, which means the scattering coefficients of the target resonate at different frequencies. Due to this effect, the performance of the conventional sparse recovery methods would decrease considerably. By utilizing the sparse learning via iterative minimization (SLIM) with the Laplace priors, we propose an effective algorithm named Laplace-SLIM to deal with the aforementioned joint sparse recovery problem, which can be seen as a kind of reweighted l1-norm algorithm. Simulation results verify the effectiveness of the proposed method and related analysis.