relation: http://www.eledia.org/students-reports/778/
title: Integrating the IMSA with Bayesian Compressive Sensing for Solving Inverse Scattering Problems
creator: Anselmi, N.
creator: Poli, L.
creator: Oliveri, G.
creator: Massa, A.
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: A novel microwave imaging technique is proposed in this work for solving 2D transverse magnetic inverse scattering problems under the first order Born approximation. The developed strategy exploits the well-known regularization capabilities of Bayesian compressive sensing (BCS) and the progressively acquired information through a multi-resolution iterative approach. Towards this end, a customized relevance vector machine (RVM) solver is implemented to iteratively improve the BCS solution accuracy within the identified region of interest (RoI). Selected numerical results are shown to verify the effectiveness of the proposed methodology.
publisher: ELEDIA Research Center - University of Trento
date: 2018
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/778/1/Integrating_the_IMSA_with_Bayesian_Compressive_Sensing_for_Solving_Inverse_Scattering_Problems.v2.pdf
identifier:   Anselmi, N. and Poli, L. and Oliveri, G. and Massa, A.  (2018) Integrating the IMSA with Bayesian Compressive Sensing for Solving Inverse Scattering Problems.  Technical Report. ELEDIA Research Center - University of Trento.