relation: http://www.eledia.org/students-reports/781/
title: Multi‐Scaling Bayesian Compressive Sensing Imaging of Dielectric Objects
creator: Anselmi, N.
creator: Poli, L.
creator: Oliveri, G.
creator: Massa, A.
subject: A WC Next Generation Wireless Communications
subject: M AT Analytic Techniques
subject: M CS Compressive Sensing
description: In this work, a new Bayesian compressive sensing (BCS)-based imaging technique is proposed to exploit additional information besides that on the target sparsity. More precisely, an innovative iterative multi-scaling (IMSA)-BCS scheme is proposed to combine the a-priori knowledge on the class of scatterers and the progressively acquired information on the location and the size of the unknown object. Accordingly the 2D transverse magnetic (TM) inverse scattering problem is solved by means of an innovative IMSA-based information-driven relevance vector machine (RVM) solver. Some numerical results are shown to verify the effectiveness of the proposed imaging technique.
publisher: ELEDIA Research Center - University of Trento
date: 2018
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/781/1/Multi-Scaling_Bayesian_Compressive_Sensing_Imaging_of_Dielectric_Objects.v2.pdf
identifier:   Anselmi, N. and Poli, L. and Oliveri, G. and Massa, A.  (2018) Multi‐Scaling Bayesian Compressive Sensing Imaging of Dielectric Objects.  Technical Report. ELEDIA Research Center - University of Trento.