摘要
无人机集群区域搜索在军事领域以及民用领域的搜救、巡逻、监测、环境勘测等方面有着广泛的应用,但如何保证不同场景下无人机集群搜索方法的效率问题依然是个难题。为了更好地解决搜索目标先验信息已知的无障碍区域内多无人机集群搜索航迹规划问题,提高无人机集群搜索效率,本文根据目标区域热度以及传感器探测概率等先验信息,提出了一种基于无人机航迹消除策略的概率计算方法,并在此基础上结合策略迭代算法动态规划无人机航迹,找到单个无人机航迹覆盖率最优策略;进而通过适当组合顺序实现无人机集群区域目标搜索整体覆盖率最优;最后,通过仿真计算验证了算法的有效性。
Multi-UAV cooperative regional search is widely used in military and civil,such as search,rescue,patrol,monitoring,and environmental survey.It is an open topic to enhance the efficiency of target search.The paper proposes a probability calculation method based on UAV track elimination strategy and policy iteration on a target region without obstacle to improve the efficiency of UAV cooperative search based on prior information.The track elimination strategy is measured by the track of the UAV and the prior information,which include detectivity of sensor as well as heat power of target region.Then heat power on the track of a single UAV is refreshed,and the track is dynamically planed by policy iteration algorithm.On the basis of the method,the tracks of all UAVs are calculated one by one with appropriate order.Finally,the effectiveness of the algorithm is verified by simulation.
作者
陈星
陈卓
杨博文
李翱翔
CHEN Xing;CHEN Zhuo;YANG Bowen;LI Aoxiang(Department of Fundamental Studies,Army Logistics Academy,Chongqing 401311 China;The 78156 Troop of PLA,Chongqing 400000,China)
出处
《指挥控制与仿真》
2024年第1期37-43,共7页
Command Control & Simulation
基金
重庆市自然科学基金项目(cstc2018jcyjAX0090)
中国人民解放军陆军勤务学院重点资助项目(LQ-ZD-202302)。
关键词
无人机集群搜索
先验信息
航迹消除
策略迭代
动态规划
Multi-UAV cooperative regional search
prior information
track elimination strategy
policy iteration
dynamically programming
