Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields
2025
Gengming Zhang | Lihua Zhang | Yitao Wang | Chunyu Kang | Yinfei Zhou | Xiaodong Ma | Zeyuan Dai | Shaxige Wu
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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