摘要
多机协同目标跟踪是无人机系统的典型任务之一.由于军事任务的集群性,在实际中常需要跟踪多个不同的目标.如何使用尽量少的无人机对多个目标实施有效跟踪,以提高系统鲁棒性和定位精度,是一个重要的研究课题.本文针对复杂环境下无人机群协同跟踪地面多目标过程中的关键问题进行研究,设计了复杂环境下无人机群协同跟踪多目标系统架构,提出了考虑遮蔽区域机群跟踪多目标动态分组算法、自适应多模型无迹卡尔曼粒子滤波融合算法和障碍条件下机群协同目标跟踪运动快速导引方法.通过仿真试验和飞行试验,验证了本文方法的有效性.最后,对该领域的下一步研究方向进行了展望.
Multi-UAV(unmanned aerial vehicle)cooperative tracking target is one of the standard exercises for unmanned aircraft systems,it is important to track multiple targets in actual missions due to the clustering of military missions.It is of great research interest and more difficult to use fewer multi-UAV to track more targets effectively,the aim of which is to be more efficient in tracking,and high precision positioning.This paper explores the key issues in the complex environment of UAV community cooperative multi-target monitoring.The architecture of the UAV group cooperative the multi-target tracking system is built in a complex environment firstly.Then a proposal was made for a dynamic grouping algorithm for multi-target UAV group tracking in an occlusion region,an adaptive multi-model unscented Kalman particle filter fusion algorithm,and a fast guidance method for cooperative target tracking in a restricted environment.The feasibility of the proposed method is validated by simulation and flight test evaluations.Finally,there is a prospect for the next course of research in this field.
作者
牛轶峰
刘俊艺
熊进
李杰
沈林成
NIU YiFeng;LIU JunYi;XIONG Jin;LI Jie;SHEN LinCheng(College of Intelligence Science and Technology,National University of Defense Technology,Changsha 410073,China;Joint Operation College,National Defense University,Shijiazhuang 050084,China)
出处
《中国科学：技术科学》
EI
CSCD
北大核心
2020年第4期403-422,共20页
Scientia Sinica(Technologica)
基金
国家自然科学基金(批准号:61876187)资助项目。
关键词
无人机群
协同控制
多目标跟踪
状态融合估计
运动导引
unmanned aerial vehicle(UAV)group
cooperative control
multi-target tracking
state fusion estimation
motion guidance
作者简介
牛轶峰,E-mail:niuyifeng@nudt.edu.cn。
