基于HS-PSO算法的水下无人集群协同探测优化部署技术  

Optimal deployment techniques of underwater unmanned swarm for cooperative detecting

作　　者：崔化超 赵玉林[1] 晏谢飞 生雪莉[2] CUI Hua-chao;ZHAO Yu-lin;YAN Xie-fei;SHENG Xue-li(The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China;College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]中国电子科技集团公司第二十八研究所,江苏南京210007 [2]哈尔滨工程大学水声工程学院,黑龙江哈尔滨150001

出　　处：《舰船科学技术》2022年第24期50-55,共6页Ship Science and Technology

摘　　要：利用水下无人集群执行协同作战任务,是未来海战场的一种新型作战样式,而优化部署技术是集群组网运用效能发挥的关键。针对水下无人集群协同探测需求,本文组合使用和声搜索算法(Harmony Search,HS)和粒子群优化算法(Particle Swarm Optimization,PSO),自动解算集群成员阵位,实现水下无人集群对任务区域的最大化有效探测覆盖。建立多约束条件下的有效探测覆盖率综合评价方法,对优化部署效果进行分析评估。仿真结果表明:HS-PSO算法具有相对稳定的全局寻优能力,与人工部署方案相比,经HS-PSO算法优化集群协同探测效能得到明显提升,可为水下无人集群智能协同任务规划提供有力支撑。Using underwater unmanned swarm to carry out cooperative mission is a new operational style in the future naval battle field. The efficiency of cluster networking mainly depends on optimal deployment techniques. In order to meet cooperative detecting requirements of underwater unmanned swarm, in this paper, the combination of harmony search(HS)and particle swarm optimization(PSO) algorithm has been used to automatically calculate the optimal parameters such as swarm member’s location. It can maximize the effective detection coverage of the task area. The comprehensive evaluation algorithm of effective detection coverage under multiple constraints is established to analyze and evaluate the optimal deployment effect. The simulation result shows that the algorithm has an relatively stable global optimization ability, and the efficiency of swarm collaborative detection optimized by HS-PSO algorithm is significantly improved, which can provide strong support for intelligent cooperative task planning of underwater unmanned swarm.

关 键 词：和声-粒子群算法 水下无人集群 协同探测 优化部署 

分 类 号：E317[军事—军事理论]