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J. Imaging 2019, 5(1), 19; https://doi.org/10.3390/jimaging5010019

Full-Vectorial 3D Microwave Imaging of Sparse Scatterers through a Multi-Task Bayesian Compressive Sensing Approach

1,2,†
,
1,2,†
and
1,2,*,†
1
ELEDIA Research Center ([email protected]—University of Trento), Via Sommarive 9, I-38123 Trento, Italy
2
ELEDIA Research Center ([email protected]—UMR 8506), 3 rue Joliot Curie, 91192 Gif-sur-Yvette, France
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 3 December 2018 / Revised: 30 December 2018 / Accepted: 8 January 2019 / Published: 15 January 2019
(This article belongs to the Special Issue Microwave Imaging and Electromagnetic Inverse Scattering Problems)
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Abstract

In this paper, the full-vectorial three-dimensional (3D) microwave imaging (MI) of sparse scatterers is dealt with. Towards this end, the inverse scattering (IS) problem is formulated within the contrast source inversion (CSI) framework and it is aimed at retrieving the sparsest and most probable distribution of the contrast source within the imaged volume. A customized multi-task Bayesian compressive sensing (MT-BCS) method is used to yield regularized solutions of the 3D-IS problem with a remarkable computational efficiency. Selected numerical results on representative benchmarks are presented and discussed to assess the effectiveness and the reliability of the proposed MT-BCS strategy in comparison with other competitive state-of-the-art approaches, as well. View Full-Text
Keywords: microwave imaging; inverse scattering; Bayesian compressive sensing (BCS); contrast source inversion (CSI); 3D microwave imaging; inverse scattering; Bayesian compressive sensing (BCS); contrast source inversion (CSI); 3D
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Salucci, M.; Poli, L.; Oliveri, G. Full-Vectorial 3D Microwave Imaging of Sparse Scatterers through a Multi-Task Bayesian Compressive Sensing Approach. J. Imaging 2019, 5, 19.

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