Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm

Abstract In order to achieve precise localization in the underwater environment, an underwater localization method based on hybrid invasive weed algorithm is proposed. First, considering the insufficient local search capability of the invasive weed algorithm, the salp swarm algorithm is used to pre‐...

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Autores principales:	Zhenkai Zhang, Yunhang Lin, Biao Jin
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/55226be397414518b327282424761ce0
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spelling	oai:doaj.org-article:55226be397414518b327282424761ce02021-11-09T04:19:38ZUnderwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm1751-86361751-862810.1049/cmu2.12277https://doaj.org/article/55226be397414518b327282424761ce02021-12-01T00:00:00Zhttps://doi.org/10.1049/cmu2.12277https://doaj.org/toc/1751-8628https://doaj.org/toc/1751-8636Abstract In order to achieve precise localization in the underwater environment, an underwater localization method based on hybrid invasive weed algorithm is proposed. First, considering the insufficient local search capability of the invasive weed algorithm, the salp swarm algorithm is used to pre‐process the initial population, the position and velocity update formulas are employed to further improve the search depth, and the hybrid invasive weed algorithm is obtained. Then, the localization error is designed as the objective function to obtain the initial value of the source, and a new localization model is built using the initial values and interference parameters. Finally, an improved two‐step weighted least square method is used to obtain the precise location of the source. The performance of the algorithm is also verified by comparisons with Cramer‐Rao Lower Bound. Simulation experiments show that the proposed algorithm has better localization accuracy than other classic methods.Zhenkai ZhangYunhang LinBiao JinWileyarticleTelecommunicationTK5101-6720ENIET Communications, Vol 15, Iss 19, Pp 2376-2389 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Zhenkai Zhang Yunhang Lin Biao Jin Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
description	Abstract In order to achieve precise localization in the underwater environment, an underwater localization method based on hybrid invasive weed algorithm is proposed. First, considering the insufficient local search capability of the invasive weed algorithm, the salp swarm algorithm is used to pre‐process the initial population, the position and velocity update formulas are employed to further improve the search depth, and the hybrid invasive weed algorithm is obtained. Then, the localization error is designed as the objective function to obtain the initial value of the source, and a new localization model is built using the initial values and interference parameters. Finally, an improved two‐step weighted least square method is used to obtain the precise location of the source. The performance of the algorithm is also verified by comparisons with Cramer‐Rao Lower Bound. Simulation experiments show that the proposed algorithm has better localization accuracy than other classic methods.
format	article
author	Zhenkai Zhang Yunhang Lin Biao Jin
author_facet	Zhenkai Zhang Yunhang Lin Biao Jin
author_sort	Zhenkai Zhang
title	Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
title_short	Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
title_full	Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
title_fullStr	Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
title_full_unstemmed	Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm
title_sort	underwater tdoa/aoa joint localization algorithm based on hybrid invasive weed optimization algorithm
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/55226be397414518b327282424761ce0
work_keys_str_mv	AT zhenkaizhang underwatertdoaaoajointlocalizationalgorithmbasedonhybridinvasiveweedoptimizationalgorithm AT yunhanglin underwatertdoaaoajointlocalizationalgorithmbasedonhybridinvasiveweedoptimizationalgorithm AT biaojin underwatertdoaaoajointlocalizationalgorithmbasedonhybridinvasiveweedoptimizationalgorithm
_version_	1718441297687085056

Underwater TDOA/AOA joint localization algorithm based on hybrid invasive weed optimization algorithm

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