基于多蚁群系统的多无人机反侦察航迹规划  

Multi-UAV Anti-reconnaissance Track Planning Based on Multi-ant Colony System

作　　者：贾雨薇 邵忻[1] JIA Yu-wei;SHAO Xin(Tianjin Foreign Studies University,Tianjin 300011,China)

机构地区：[1]天津外国语大学,天津300011

出　　处：《舰船电子对抗》2023年第3期14-19,共6页Shipboard Electronic Countermeasure

摘　　要：无人机侦察具有机动性强、定位精度高等优势,可有效弥补航天侦察过境时间受限和技术侦察难以定位电磁静默目标的不足。搭载机载雷达侦察系统的多架无人机协同对热点区域搜索,“以空侦海”可大幅提升联合作战行动中对海搜索侦察能力。因此,无人机协同海域态势感知路径规划问题研究具有重大意义。提出了基于Markov Mento-Carlo仿真+多类型蚁群系统算法的多无人机协同搜索方法,并根据概率热图提供的先验概率以及机动策略,提出了基于贝叶斯的概率图更新策略。Unmanned air vehicle(UAV)reconnaissance has the advantages of strong mobility and high positioning accuracy,etc.,which can effectively make up for the limitation of transit time of space reconnaissance and the difficulty to locate electromagnetic silent targets by means of technical reconnaissance.Multiple UAVs carrying airborne radar reconnaissance system cooperate to search for hot areas,“detecting the surface with air”,which can greatly improve the capability of sea search and reconnaissance in joint operations.Therefore,the research into the problem of UAV coordinated situational awareness path planning in sea area is of great significance.In this paper,a multi-UAV collaborative search method based on Markov Mento-Carlo simulation+multi-type ant colony system algorithm is proposed,and a Bayesian-based probabilistic graph update strategy is proposed according to the pre-probability and maneuverable strategy provided by the probability thermal map.

关 键 词：仿真建模 多蚁群算法 蒙特卡洛仿真 

分 类 号：TN971.1[电子电信—信号与信息处理]