匹配场目标定位的并行遗传算法实现

摘要

In view of the parallelism of a matched field localization algorithm,the frame of a parallel computing algorithm was constructed in the match field localization,and the parallel genetic algorithm was introduced as the optimization tool of matched field processing.In order to achieve rapid convergence,the operators and evaluation criteria of the genetic algorithm were designed based on the actual characteristics of matched field processing.A parallel algorithm was tested and analyzed in the Windows XP operating system and the MPI parallel environment,with internet-connected dual-core PC machines as the parallel computing hardware platform.The results show that the parallel genetic algorithm method is better than the traditional mesh method in matched field localization,and can effectively save algorithm running time while achieving fast sound positioning.%针对匹配场声源定位算法中存在的固有并行性,构建了匹配场声源定位的并行计算算法框架,并引入并行遗传算法作为匹配场处理的寻优工具.根据匹配场处理的实际特性,对并行遗传算法的操作算子及评估标准进行了合理设计,使其快速收敛.以网络互联的双核PC机作为并行计算硬件平台,在Windows XP操作系统和MPI并行环境中对匹配场定位的并行算法进行了测试和分析.研究表明:采用并行遗传算法实现匹配场声源定位方法优于传统网格法,可有效节省算法运行时间,快速实现声源定位.