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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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/6/1020 |
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| _version_ | 1849432546087010304 |
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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. |
| format | Article |
| 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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