摘要
针对不确定环境下无人机区域搜索问题,建立了实时探测更新的搜索方法,提出了机载光电载荷参数优化配置策略。建立了基于二维离散网格的无人机区域搜索模型,采用概率地图描述目标信息的实时获取与更新;引入不确定度指标、目标网格的重访和网格探测次数控制,建立搜索目标函数;建立了基于粒子群算法的搜索路径滚动优化方法;通过对任务区域平均探测时间步数和误判概率的估计分析,建立了机载光电载荷参数优化配置策略。使用蒙特卡洛方法验证了区域搜索方法的有效性和光电载荷参数配置对搜索效率、误判概率的影响。
A real-time detecting and updating search strategy was presented for UAV area target search in uncertain environment,and an optimal configuration method of airborne photoelectric load parameters was proposed.An area target search model based on a two-dimensional discrete grid was established,and a probability map was used to describe the real-time acquisition and update of target information.A search objective function was built with the introducing of uncertainty index,revisiting of grid with target and controlling of grid detection times.The search route planning method based on particle swarm optimization was established.Through the estimation and analysis of average detection time and misjudgement probability of the task area,the optimal configuration strategy of airborne photoelectric load parameters was proposed.The Monte Carlo method was used to verify the effectiveness of the area target search method and the effect of photoelectric load parameter configuration on search efficiency and misjudgement probability.
作者
吴岸平
郭正
侯中喜
鲁亚飞
WU Anping;GUO Zheng;HOU Zhongxi;LU Yafei(College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China)
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2020年第4期35-42,共8页
Journal of National University of Defense Technology
基金
国家自然科学基金资助项目(61703414)。
关键词
目标搜索
概率地图
路径规划
载荷参数配置
target search
probability map
route planning
payload parameters configuration
