基于人工势场-蚁群融合算法的水下航行器声隐蔽航路规划OA北大核心

Underwater vehicle route planning faces two main challenges:the"unreachability"problem in the clas-sical ant colony algorithm and insufficient consideration of acoustic concealment requirements.To address these is-sues,an artificial potential field-ant colony fusion algorithm was proposed for planning routes that ensure acoustic concealment based on sound field distribution.First,the sound field distribution in an undulating seafloor environ-ment was calculated,and the probability distribution of detection was determined.This information was then incor-porated into the heuristic function as concealment heuristic data.By integrating the potential field heuristic from the artificial potential field method,a potential field force heuristic function was constructed to avoid local optima through the potential field decay coefficient.Finally,the fusion algorithm was used to achieve global optimal route planning.The results show that the fusion algorithm effectively resolves the"unreachability"problem of the ant col-ony algorithm in complex environments.Additionally,the convergence speed is improved by 22.66%,with better stability in convergence.The acoustic concealment of the route is also ensured,making this approach a valuable reference for hidden route planning of underwater vehicles.