Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields

To tackle the problem of existing underwater vehicle covert path planning methods ignoring ambient noise fields, an automated path planning method based on a statistically characterized environmental noise field is proposed. The method involves constructing a background noise spectrum level model us...

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Main Authors: Gengming Zhang, Lihua Zhang, Yitao Wang, Chunyu Kang, Yinfei Zhou, Xiaodong Ma, Zeyuan Dai, Shaxige Wu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/13/6/1020
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author Gengming Zhang
Lihua Zhang
Yitao Wang
Chunyu Kang
Yinfei Zhou
Xiaodong Ma
Zeyuan Dai
Shaxige Wu
author_facet Gengming Zhang
Lihua Zhang
Yitao Wang
Chunyu Kang
Yinfei Zhou
Xiaodong Ma
Zeyuan Dai
Shaxige Wu
author_sort Gengming Zhang
collection DOAJ
description To tackle the problem of existing underwater vehicle covert path planning methods ignoring ambient noise fields, an automated path planning method based on a statistically characterized environmental noise field is proposed. The method involves constructing a background noise spectrum level model using Automatic Identification System (AIS) data and wind speed data. Then, a Range-Dependent Acoustic Model (RAM) is integrated to generate a statistically significant 10th percentile noise field. The result is subsequently incorporated into the sonar equation to develop a noise-considerate concealment effectiveness model, which serves as input for a noise-considerate A* path planning algorithm. Comparative analyses of path planning results demonstrate that, within the studied maritime domain, the noise-prioritized path exhibits a statistically significant reduction in the median detection range by approximately 17%, a 50% reduction in the minimum detection range, and a 20% reduction in the maximum detection range, relative to alternative paths planned with a fixed noise level assumption.
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id doaj-art-0347161de65c4c209557c02094cd4cb8
institution Kabale University
issn 2077-1312
language English
publishDate 2025-05-01
publisher MDPI AG
record_format Article
series Journal of Marine Science and Engineering
spelling doaj-art-0347161de65c4c209557c02094cd4cb82025-08-20T03:27:19ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-05-01136102010.3390/jmse13061020Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise FieldsGengming Zhang0Lihua Zhang1Yitao Wang2Chunyu Kang3Yinfei Zhou4Xiaodong Ma5Zeyuan Dai6Shaxige Wu7Department of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaSoftware and Simulation Institute, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Water Weapons and Chemical Protection, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaTo tackle the problem of existing underwater vehicle covert path planning methods ignoring ambient noise fields, an automated path planning method based on a statistically characterized environmental noise field is proposed. The method involves constructing a background noise spectrum level model using Automatic Identification System (AIS) data and wind speed data. Then, a Range-Dependent Acoustic Model (RAM) is integrated to generate a statistically significant 10th percentile noise field. The result is subsequently incorporated into the sonar equation to develop a noise-considerate concealment effectiveness model, which serves as input for a noise-considerate A* path planning algorithm. Comparative analyses of path planning results demonstrate that, within the studied maritime domain, the noise-prioritized path exhibits a statistically significant reduction in the median detection range by approximately 17%, a 50% reduction in the minimum detection range, and a 20% reduction in the maximum detection range, relative to alternative paths planned with a fixed noise level assumption.https://www.mdpi.com/2077-1312/13/6/1020ship noisewind-generated noisecovert pathunderwater vehicle
spellingShingle Gengming Zhang
Lihua Zhang
Yitao Wang
Chunyu Kang
Yinfei Zhou
Xiaodong Ma
Zeyuan Dai
Shaxige Wu
Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
Journal of Marine Science and Engineering
ship noise
wind-generated noise
covert path
underwater vehicle
title Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
title_full Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
title_fullStr Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
title_full_unstemmed Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
title_short Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
title_sort method for automatic path planning of underwater vehicles considering ambient noise fields
topic ship noise
wind-generated noise
covert path
underwater vehicle
url https://www.mdpi.com/2077-1312/13/6/1020
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