Heuristic Search for Moving Underwater Targets Based on Markov Process
基于马尔可夫过程的水下运动目标启发式搜索

If there are obstacles in the search sea area, the heuristic search algorithm can be applied into the search process of moving underwater targets, to study the heuristic search for moving underwater targets based on Markov process in this paper. The Markov process motion model of underwater targets, the heuristic search model and search probability model of searcher are built. This algorithm continually estimates and updates the moving underwater targets location based on the target’s prior location distributed information, to gain accurate targets posterior location distribution information, by using the heuristic function to get the next best search node. The simulation shows that the heuristic search can avoid obstacles effectively, when searching the moving underwater targets. Moreover, it can improve search efficiency. It is useful to study on optimization search for moving underwater targets.