Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach

An innovative inverse scattering (<i>IS</i>) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (<i>GPR</i>) data by joint...

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Autores principales:	Marco Salucci, Nicola Anselmi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	inverse scattering (<i>IS</i>) microwave imaging (<i>MI</i>) ground penetrating radar (<i>GPR</i>) multi-frequency (<i>MF</i>) multi-task Bayesian compressive sensing (<i>MT-BCS</i>) Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/5ce6ed4ad3314a5993fe5b473376be69
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spelling	oai:doaj.org-article:5ce6ed4ad3314a5993fe5b473376be692021-11-25T18:03:36ZMulti-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach10.3390/jimaging71102472313-433Xhttps://doaj.org/article/5ce6ed4ad3314a5993fe5b473376be692021-11-01T00:00:00Zhttps://www.mdpi.com/2313-433X/7/11/247https://doaj.org/toc/2313-433XAn innovative inverse scattering (<i>IS</i>) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (<i>GPR</i>) data by jointly processing the multi-frequency (<i>MF</i>) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian compressive sensing (<i>MT-BCS</i>) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed <i>MF-MT-BCS</i> strategy also in comparison with competitive state-of-the-art alternatives.Marco SalucciNicola AnselmiMDPI AGarticleinverse scattering (<i>IS</i>)microwave imaging (<i>MI</i>)ground penetrating radar (<i>GPR</i>)multi-frequency (<i>MF</i>)multi-task Bayesian compressive sensing (<i>MT-BCS</i>)PhotographyTR1-1050Computer applications to medicine. Medical informaticsR858-859.7Electronic computers. Computer scienceQA75.5-76.95ENJournal of Imaging, Vol 7, Iss 247, p 247 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	inverse scattering (<i>IS</i>) microwave imaging (<i>MI</i>) ground penetrating radar (<i>GPR</i>) multi-frequency (<i>MF</i>) multi-task Bayesian compressive sensing (<i>MT-BCS</i>) Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
spellingShingle	inverse scattering (<i>IS</i>) microwave imaging (<i>MI</i>) ground penetrating radar (<i>GPR</i>) multi-frequency (<i>MF</i>) multi-task Bayesian compressive sensing (<i>MT-BCS</i>) Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95 Marco Salucci Nicola Anselmi Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
description	An innovative inverse scattering (<i>IS</i>) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (<i>GPR</i>) data by jointly processing the multi-frequency (<i>MF</i>) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian compressive sensing (<i>MT-BCS</i>) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed <i>MF-MT-BCS</i> strategy also in comparison with competitive state-of-the-art alternatives.
format	article
author	Marco Salucci Nicola Anselmi
author_facet	Marco Salucci Nicola Anselmi
author_sort	Marco Salucci
title	Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
title_short	Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
title_full	Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
title_fullStr	Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
title_full_unstemmed	Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach
title_sort	multi-frequency gpr microwave imaging of sparse targets through a multi-task bayesian compressive sensing approach
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5ce6ed4ad3314a5993fe5b473376be69
work_keys_str_mv	AT marcosalucci multifrequencygprmicrowaveimagingofsparsetargetsthroughamultitaskbayesiancompressivesensingapproach AT nicolaanselmi multifrequencygprmicrowaveimagingofsparsetargetsthroughamultitaskbayesiancompressivesensingapproach
_version_	1718411681610072064

Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach

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