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Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar

A compressed sensing/sparse-recovery procedure is adopted to obtain enhanced range resolution capability from the processing of data acquired with narrow-band SFCW radars. A mathematical formulation for the proposed approach is reported and validity limitations are fully discussed, by demonstrating...

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Autor principal: Costanzo, Sandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753000/
https://www.ncbi.nlm.nih.gov/pubmed/27022617
http://dx.doi.org/10.1155/2016/3137146
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author Costanzo, Sandra
author_facet Costanzo, Sandra
author_sort Costanzo, Sandra
collection PubMed
description A compressed sensing/sparse-recovery procedure is adopted to obtain enhanced range resolution capability from the processing of data acquired with narrow-band SFCW radars. A mathematical formulation for the proposed approach is reported and validity limitations are fully discussed, by demonstrating the ability to identify a great number of targets, up to 20, in the range direction. Both numerical and experimental validations are presented, by assuming also noise conditions. The proposed method can be usefully applied for the accurate detection of parameters with very small variations, such as those involved in the monitoring of soil deformations or biological objects.
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spelling pubmed-47530002016-03-28 Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar Costanzo, Sandra ScientificWorldJournal Research Article A compressed sensing/sparse-recovery procedure is adopted to obtain enhanced range resolution capability from the processing of data acquired with narrow-band SFCW radars. A mathematical formulation for the proposed approach is reported and validity limitations are fully discussed, by demonstrating the ability to identify a great number of targets, up to 20, in the range direction. Both numerical and experimental validations are presented, by assuming also noise conditions. The proposed method can be usefully applied for the accurate detection of parameters with very small variations, such as those involved in the monitoring of soil deformations or biological objects. Hindawi Publishing Corporation 2016 2016-01-31 /pmc/articles/PMC4753000/ /pubmed/27022617 http://dx.doi.org/10.1155/2016/3137146 Text en Copyright © 2016 Sandra Costanzo. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Costanzo, Sandra
Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title_full Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title_fullStr Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title_full_unstemmed Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title_short Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar
title_sort compressed sensing/sparse-recovery approach for improved range resolution in narrow-band radar
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753000/
https://www.ncbi.nlm.nih.gov/pubmed/27022617
http://dx.doi.org/10.1155/2016/3137146
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