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Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars
The problem of obtaining high range resolution (HRR) profiles for non-cooperative target recognition by coherently combining data from narrowband radars was investigated using sparse reconstruction techniques. If the radars concerned operate within different frequency bands, then this process increa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038352/ https://www.ncbi.nlm.nih.gov/pubmed/31991710 http://dx.doi.org/10.3390/s20030665 |
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author | Berry, Paul Nguyen, Ngoc Hung Tran, Hai-Tan |
author_facet | Berry, Paul Nguyen, Ngoc Hung Tran, Hai-Tan |
author_sort | Berry, Paul |
collection | PubMed |
description | The problem of obtaining high range resolution (HRR) profiles for non-cooperative target recognition by coherently combining data from narrowband radars was investigated using sparse reconstruction techniques. If the radars concerned operate within different frequency bands, then this process increases the overall effective bandwidth and consequently enhances resolution. The case of unknown range offsets occurring between the radars’ range profiles due to incorrect temporal and spatial synchronisation between the radars was considered, and the use of both pruned orthogonal matching pursuit and refined [Formula: see text]-norm regularisation solvers was explored to estimate the offsets between the radars’ channels so as to attain the necessary coherence for combining their data. The proposed techniques were demonstrated and compared using simulated radar data. |
format | Online Article Text |
id | pubmed-7038352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70383522020-03-09 Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars Berry, Paul Nguyen, Ngoc Hung Tran, Hai-Tan Sensors (Basel) Article The problem of obtaining high range resolution (HRR) profiles for non-cooperative target recognition by coherently combining data from narrowband radars was investigated using sparse reconstruction techniques. If the radars concerned operate within different frequency bands, then this process increases the overall effective bandwidth and consequently enhances resolution. The case of unknown range offsets occurring between the radars’ range profiles due to incorrect temporal and spatial synchronisation between the radars was considered, and the use of both pruned orthogonal matching pursuit and refined [Formula: see text]-norm regularisation solvers was explored to estimate the offsets between the radars’ channels so as to attain the necessary coherence for combining their data. The proposed techniques were demonstrated and compared using simulated radar data. MDPI 2020-01-24 /pmc/articles/PMC7038352/ /pubmed/31991710 http://dx.doi.org/10.3390/s20030665 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Berry, Paul Nguyen, Ngoc Hung Tran, Hai-Tan Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title | Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title_full | Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title_fullStr | Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title_full_unstemmed | Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title_short | Compressive Sensing-Based Bandwidth Stitching for Multichannel Microwave Radars |
title_sort | compressive sensing-based bandwidth stitching for multichannel microwave radars |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038352/ https://www.ncbi.nlm.nih.gov/pubmed/31991710 http://dx.doi.org/10.3390/s20030665 |
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