基于协同进化算法的多舰扩方应召反潜搜索方法

Optimal Extended Position Call Search Method for Multi-ships Based on Cooperative Evolution Algorithm

反潜作战是现代海战中水面舰艇的主要作战任务之一,对潜搜索行动是水面舰艇反潜作战的重要组成部分,是实施对潜攻击的前提和保证。针对目前常规多舰扩方搜索方法存在搜索效率低、协同能力弱的问题,对现有的2种多舰扩方搜索样式进行协同路径优化。根据舰艇声呐搜索原理以及实际反潜战术的应用,以在固定搜索时长内使得搜索效能最大为目标,建立了2种搜索样式最优协同路径问题的数学规划模型,给出了运用改进的协同进化算法规划多艘舰艇搜索路径的具体求解过程,并通过仿真实验得到不同搜索样式下的多舰协同最优搜索路径。结果表明:该方法具有搜索范围大、搜索效率高的特点,相比常规方法具有较大优势,适用于解决多舰扩方反潜搜索路径规划问题。

Anti-submarine warfare is one of the main combat missions of surface naval warship in modern naval warfare. Submarine search is an important part of surface warship anti-submarine warfare and is the prerequisite and guarantee for the implementation of anti-submarine attack. Aiming at the conventional multi-ships extend position call search method has low search efficiency and weak coordination ability, the cooperative path optimization of the existing two kinds of multi-ship search methods is carried out. According to the principle of naval sonar search and the application of actual anti-submarine tactics, the mathematical programming model of two kinds of search pattern optimal cooperative path problem is established with the aim of maximizing the search performance in the fixed search time, the concrete solution of multiple ship search paths is given by using the improved co-evolutionary algorithm, and the multi-ship cooperative optimal search path under different search styles is obtained by simulation experiment. The results show that the method has the advantages of large searching range and high searching efficiency compared with conventional methods, which is suitable for solving the multi-ship anti-submarine search path planning problem.