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中文摘要：
在对启发式搜索算法进行研究的基础上,建立了水下目标的马尔可夫过程运动模型,将启发式搜索算法应用于对水下运动目标的搜索,研究了基于马尔可夫过程的运动目标启发式搜索算法。该算法由已知的目标先验位置分布信息不断地对目标的运动位置进行估计、更新,以获得精确的目标后验分布,再利用启发函数得到下一步的最佳搜索节点。仿真分析表明：在对水下运动目标搜索时,启发式搜索优于扩展方形搜索和平行搜索,有效地改善了搜索时间和搜索效率。
英文摘要：
On the basis of studying the heuristic search algorithm, the Markov process motion model of underwater targets was set up. The heuristic search algorithm was applied to the search of moving underwater targets, to s~udy the heuristic search for moving underwater targets based on Markov process. The algorithm continually estimates and updates the moving underwater targets location based on the target location distributed information, to gain accurate target posterior distribution, uses heuristic function to get the next optimal search node. The simulated result shows that the heuristic search is superior to the expanded square search and the parallel search, and improvs search time and search efficiency effectively.
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