Contrast Source Inversion of Sparse Targets through Multi-Resolution Bayesian Compressive Sensing

The retrieval of non-Born scatterers is addressed within the contrast source inversion (CSI) framework by means of a novel multi-step inverse scattering method that jointly exploits prior information on the class of targets under investigation and progressively-acquired knowledge on the domain under investigation. The multi-resolution (MR) representation of the unknown contrast sources is iteratively retrieved by applying a Bayesian compressive sensing (BCS) sparsity-promoting approach based on a constrained relevance vector machine solver. Representative examples of inversions from synthetic and experimental data are reported to give some indications on the reliability and the robustness of the proposed MR-BCS-CSI method. Comparisons with recent and competitive state-of-the-art alternatives are reported, as well.