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Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing

Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the...

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Autores principales: Shi, Zhibo, Liang, Guolong, Qiu, Longhao, Wan, Guangming, Zhao, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731401/
https://www.ncbi.nlm.nih.gov/pubmed/33291843
http://dx.doi.org/10.3390/s20236949
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author Shi, Zhibo
Liang, Guolong
Qiu, Longhao
Wan, Guangming
Zhao, Lei
author_facet Shi, Zhibo
Liang, Guolong
Qiu, Longhao
Wan, Guangming
Zhao, Lei
author_sort Shi, Zhibo
collection PubMed
description Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the design of the vector hydrophone array. The difference between the vector hydrophone array and the scalar hydrophone array is that each vector hydrophone has three or four channels. When designing a sparse vector hydrophone array, these channels need to be optimized at the same time to ensure the sparsity of the array elements’ number. To solve this problem, this paper introduced the compressed sensing (CS) theory into the vector hydrophone array design, constructed the vector hydrophone array design problem into a globally solvable optimization problem, proposed a CS-based algorithm with the L(1) norm suitable for vector hydrophone array, and realized the simultaneous optimization of multiple channels from the same vector hydrophone. At the same time, the off-grid algorithm was added to obtain higher design accuracy. Two design examples verify the effectiveness of the proposed method. The theoretical analysis and simulation results show that compared with the conventional compressed sensing algorithm with the same aperture, the algorithm proposed in this paper used fewer vector hydrophone elements to obtain better fitting of the desired beam pattern.
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spelling pubmed-77314012020-12-12 Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing Shi, Zhibo Liang, Guolong Qiu, Longhao Wan, Guangming Zhao, Lei Sensors (Basel) Article Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the design of the vector hydrophone array. The difference between the vector hydrophone array and the scalar hydrophone array is that each vector hydrophone has three or four channels. When designing a sparse vector hydrophone array, these channels need to be optimized at the same time to ensure the sparsity of the array elements’ number. To solve this problem, this paper introduced the compressed sensing (CS) theory into the vector hydrophone array design, constructed the vector hydrophone array design problem into a globally solvable optimization problem, proposed a CS-based algorithm with the L(1) norm suitable for vector hydrophone array, and realized the simultaneous optimization of multiple channels from the same vector hydrophone. At the same time, the off-grid algorithm was added to obtain higher design accuracy. Two design examples verify the effectiveness of the proposed method. The theoretical analysis and simulation results show that compared with the conventional compressed sensing algorithm with the same aperture, the algorithm proposed in this paper used fewer vector hydrophone elements to obtain better fitting of the desired beam pattern. MDPI 2020-12-04 /pmc/articles/PMC7731401/ /pubmed/33291843 http://dx.doi.org/10.3390/s20236949 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
Shi, Zhibo
Liang, Guolong
Qiu, Longhao
Wan, Guangming
Zhao, Lei
Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title_full Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title_fullStr Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title_full_unstemmed Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title_short Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing
title_sort vector hydrophone array design based on off-grid compressed sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731401/
https://www.ncbi.nlm.nih.gov/pubmed/33291843
http://dx.doi.org/10.3390/s20236949
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AT wanguangming vectorhydrophonearraydesignbasedonoffgridcompressedsensing
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