relation: http://www.eledia.org/students-reports/911/
title: Multi-Resolution Bayesian Compressive Sensing for Sparse Target Inversion
creator: SALUCCI, Marco
creator: POLI, Lorenzo
creator: ZARDI, Francesco
creator: TOSI, Luca
creator: LUSA, Samantha
creator: MASSA, Andrea
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: Non-Born scatterer retrieval is addressed within the contrast source inversion (CSI) framework using a novel multi-step inverse scattering approach. The unknown contrast sources are represented in a multi-resolution (MR) framework and iteratively reconstructed using a Bayesian compressive sensing (BCS) approach, which employs a constrained relevance vector machine solver to promote sparsity. To assess the reliability and robustness of the proposed MR-BCS-CSI method, representative inversions from both synthetic and experimental data are presented. Additionally, comparisons with recent state-of-the-art alternatives are provided.
publisher: ELEDIA Research Center - University of Trento
date: 2025
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/911/1/Multi-Resolution_Bayesian_Compressive_Sensing_for_Sparse_Target_Inversion.pdf
identifier:   SALUCCI, Marco and POLI, Lorenzo and ZARDI, Francesco and TOSI, Luca and LUSA, Samantha and MASSA, Andrea  (2025) Multi-Resolution Bayesian Compressive Sensing for Sparse Target Inversion.  Technical Report. ELEDIA Research Center - University of Trento.