M. Salucci, L. Poli, F. Zardi, L. Tosi, Samantha Lusa, A. Massa
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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 (IS) 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 (C-RVM) 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 (SoA) alternatives are reported, as well.
期刊介绍:
An interdisciplinary journal combining mathematical and experimental papers on inverse problems with theoretical, numerical and practical approaches to their solution.
As well as applied mathematicians, physical scientists and engineers, the readership includes those working in geophysics, radar, optics, biology, acoustics, communication theory, signal processing and imaging, among others.
The emphasis is on publishing original contributions to methods of solving mathematical, physical and applied problems. To be publishable in this journal, papers must meet the highest standards of scientific quality, contain significant and original new science and should present substantial advancement in the field. Due to the broad scope of the journal, we require that authors provide sufficient introductory material to appeal to the wide readership and that articles which are not explicitly applied include a discussion of possible applications.