基于分布式融合定位的无人机集群自组织协同飞行控制方法  

Self-organized Cooperative Flight Control Method for UAV Swarms Based on Distributed Fusion Positioning

作　　者：李晨玮 周建山[1] 田大新[1] 段续庭[1] 赵德宗 任成昊 LI Chenwei;ZHOU Jianshan;TIAN Daxin;DUAN Xuting;ZHAO Dezong;REN Chenghao(School of Transportation Science and Engineering,Beihang University,Beijing 100191,China;James Watt School of Engineering,University of Glasgow,UK;Zibo Wayou Chuangfei Intelligent Technology Co.,Ltd,Zibo 255049,China)

机构地区：[1]北京航空航天大学交通科学与工程学院,北京100191 [2]格拉斯哥大学工程学院,英国 [3]淄博哇呦创飞智能科技有限公司,淄博255049

出　　处：《无人系统技术》2023年第5期61-70,共10页Unmanned Systems Technology

基　　金：国家自然科学基金(52202391、U20A20155)。

摘　　要：针对无人机集群如何精确估计目标位置并协同打击目标的问题,开展了无人机集群自组织协同飞行控制方法研究。考虑噪声对定位精度的影响,建立了无人机对目标位置的含噪测量模型,设计了无人机集群自主协同移动算法。具体地,首先建立无人机集群对目标位置进行测量的全局误差最小化模型,结合梯度下降的更新机制和加权融合机制,提出了分布式感知融合算法,实现无人机集群对目标位置以及集群平均飞行速度的精确估计;在此基础上,提出了具有自适应能力的无人机位置、速度控制策略,实现集群自主协同飞行。仿真结果表明,提出的算法可以有效降低噪声干扰,显著提高无人机对目标位置和集群平均速度的测量精度,集群向多个目标点飞行的条件下,无人机对目标位置测量的均方偏差降低95%,对平均速度测量的均方偏差降低183%,实现无人机集群的自组织协同飞行控制。Aiming at the problem of how UAV swarms can accurately estimate the target position and strike the target cooperatively,research on the self-organized cooperative flight control method of UAV swarms is carried out.Considering the influence of noise on positioning accuracy,a noise-containing measurement model of UAV on the target position is established,and an autonomous cooperative movement algorithm for UAV swarms is designed.Specifically,firstly,a global error minimization model for the measurement of target position by UAV swarms is established,and a distributed sensory fusion algorithm is proposed in combination with the gradient descent update mechanism and the weighted fusion mechanism to realize the accurate estimation of target position and the average flight speed of swarms by UAV swarms.On this basis,a UAV position and speed control strategy with self-adaptive capability is proposed to realize autonomous cooperative swarms flight.Simulation results show that the proposed algorithm can effectively reduce the noise interference,significantly improve the measurement accuracy of target position and clusters average speed of UAVs.Under the condition of clusters flying to multiple target points,the MSD of UAV on target position measurement is reduced by 95%,and the MSD of UAV on average speed measurement is reduced by 183%,and realize the self-organized collaborative flight control of UAV clusters.

关 键 词：无人机集群 抗干扰 协同飞行 分布式感知融合 目标测量 运动控制策略 

分 类 号：V279[航空宇航科学与技术—飞行器设计]