relation: http://www.eledia.org/students-reports/742/
title: Innovative Alphabet‐Based Bayesian Compressive Sensing Technique for Imaging Targets with Arbitrary Shape
creator: Anselmi, N.
creator: Oliveri, G.
creator: Hannan, M.
creator: Salucci, M.
creator: Massa, A.
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: In this work an innovative two-dimensional (2D) microwave imaging technique exploiting Bayesian Compressive Sensing (BCS) and a wavelet-based alphabet for representing the problem unknowns is dealt with. The proposed approach is based on the generalization of the sparsity concept, extending the range of applicability of BCS-based inverse scattering (IS) techniques to objects with arbitrary shape and dimensions. A set of BCS reconstructions is performed considering different expansion bases in the alphabet, without the need for a-priori knowledge about the unknown scatterers. Then, the best reconstruction is recognized as that minimizing the number of non-null retrieved coefficients (i.e., the sparsest one). In order to verify the effectiveness of the proposed imaging technique, a set of representative numerical benchmarks is presented. Some comparisons with state-of-the-art IS techniques are presented, as well.
publisher: ELEDIA Research Center - University of Trento
date: 2017
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/742/1/Innovative_Alphabet%E2%80%90Based_Bayesian_Compressive_Sensing_Technique_for_Imaging_Targets_with_Arbitrary_Shape.v2.pdf
identifier:   Anselmi, N. and Oliveri, G. and Hannan, M. and Salucci, M. and Massa, A.  (2017) Innovative Alphabet‐Based Bayesian Compressive Sensing Technique for Imaging Targets with Arbitrary Shape.  Technical Report. ELEDIA Research Center - University of Trento.