Research on Path Optimization for Underwater Target Search Under the Constraint of Sea Surface Wind Field

With the increasing frequency of marine activities, the significance of underwater target search and rescue has been highlighted, where precise and efficient path planning is critical for ensuring search effectiveness. This study proposes an underwater target search path planning method by incorporating the dynamic variations of marine acoustic environments driven by sea surface wind fields. First, wind-generated noise levels are calculated based on the sea surface wind field data of the mission area, and transmission loss is solved using an underwater acoustic propagation ray model. Then, a spatially variant search distance matrix is constructed by integrating the active sonar equation. Finally, a sixteen-azimuth path planning model is established, and a genetic algorithm (GA) is introduced to optimize the search path for maximum coverage. Numerical simulations in three typical sea areas (the South China Sea, Atlantic Ocean, and Pacific Ocean) demonstrate that the optimized search coverage of the proposed method increases by 54.32%–130.22% compared with the pre-optimization results, providing an efficient and feasible solution for underwater target search.