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Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy

This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric...

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Detalles Bibliográficos
Autores principales: Li, Yuhan, Ruan, Ruizhi, Zhou, Zupeng, Sun, Anqing, Luo, Xiaonan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181554/
https://www.ncbi.nlm.nih.gov/pubmed/37177602
http://dx.doi.org/10.3390/s23094398
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author Li, Yuhan
Ruan, Ruizhi
Zhou, Zupeng
Sun, Anqing
Luo, Xiaonan
author_facet Li, Yuhan
Ruan, Ruizhi
Zhou, Zupeng
Sun, Anqing
Luo, Xiaonan
author_sort Li, Yuhan
collection PubMed
description This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric model and divides the positioning process into four steps, including data preprocessing to detect geometric errors and apply mean filtering, direction capture, position tracking, and position synchronization. To achieve these steps, a new adaptive tracking control algorithm is proposed that does not require trajectory prediction and is applied to the last three steps. The algorithm is deployed to the buoy for tracking simulation and sea trial experiments, and the results are compared with those of a model predictive control algorithm. The autonomous tracking buoy based on the adaptive tracking control algorithm runs more stably and can better complete the precise tracking task for the UUV with a positioning error of less than 10 cm. This method breaks the premise of trajectory prediction based on traditional tracking control algorithms, providing a new direction for further research on UUV localization. Furthermore, the conclusion of this paper has important reference value for other research and application fields related to UUV.
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spelling pubmed-101815542023-05-13 Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy Li, Yuhan Ruan, Ruizhi Zhou, Zupeng Sun, Anqing Luo, Xiaonan Sensors (Basel) Article This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric model and divides the positioning process into four steps, including data preprocessing to detect geometric errors and apply mean filtering, direction capture, position tracking, and position synchronization. To achieve these steps, a new adaptive tracking control algorithm is proposed that does not require trajectory prediction and is applied to the last three steps. The algorithm is deployed to the buoy for tracking simulation and sea trial experiments, and the results are compared with those of a model predictive control algorithm. The autonomous tracking buoy based on the adaptive tracking control algorithm runs more stably and can better complete the precise tracking task for the UUV with a positioning error of less than 10 cm. This method breaks the premise of trajectory prediction based on traditional tracking control algorithms, providing a new direction for further research on UUV localization. Furthermore, the conclusion of this paper has important reference value for other research and application fields related to UUV. MDPI 2023-04-29 /pmc/articles/PMC10181554/ /pubmed/37177602 http://dx.doi.org/10.3390/s23094398 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Yuhan
Ruan, Ruizhi
Zhou, Zupeng
Sun, Anqing
Luo, Xiaonan
Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title_full Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title_fullStr Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title_full_unstemmed Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title_short Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
title_sort positioning of unmanned underwater vehicle based on autonomous tracking buoy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181554/
https://www.ncbi.nlm.nih.gov/pubmed/37177602
http://dx.doi.org/10.3390/s23094398
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