relation: http://www.eledia.org/students-reports/915/
title: An Iterative Bayesian Compressive Sensing Approach for reconstructing Non-Born Scatterer
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: This study presents an advanced multi-step inverse scattering method, developed within the contrast source inversion (CSI) framework, to reconstruct non-Born scatterers. The technique utilizes a multi-resolution (MR) model to represent the contrast sources, which are progressively estimated using a Bayesian compressive sensing (BCS) strategy with sparsity constraints. The proposed MR-BCS-CSI method is thoroughly tested using simulated data to validate its precision and stability. Comparative evaluations against current state-of-the-art techniques reveal the method’s strong performance and reliability.
publisher: ELEDIA Research Center - University of Trento
date: 2025
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/915/1/An_Iterative_Bayesian_Compressive_Sensing_Approach_for_reconstructing_Non-Born_Scatterer.pdf
identifier:   SALUCCI, Marco and POLI, Lorenzo and ZARDI, Francesco and TOSI, Luca and LUSA, Samantha and MASSA, Andrea  (2025) An Iterative Bayesian Compressive Sensing Approach for reconstructing Non-Born Scatterer.  Technical Report. ELEDIA Research Center - University of Trento.