一种基于分簇的集群协同定位系统

A clustering⁃based cooperative localization system for swarm

随着硬件平台的进步和通信控制技术的发展,无人集群系统在民用和军用领域的应用越来越广泛。集群通过编队控制执行任务,而高效精准的定位是实现集群编队控制的基础。针对在全球导航卫星系统拒止/受限和非视距条件下执行大规模、高动态的集群定位场景,文中通过集群控制手段,构建了一套基于分簇的定位系统。该系统引入了测距时序优化方案和矩阵填充优化算法,通过卡尔曼滤波算法执行测量误差优化,为每个节点以高鲁棒性和灵活性提供高精度的相对位置估计。基于所提定位系统,文中设计了一套基于超宽带(UWB)的硬件设备,并通过场地实测,结合高效精准的标定方法,验证了所提出的定位系统的有效性。

Thanks to the progress on hardware platforms and communication control technologies,swarm systems have been widely used in civil and military fields.Based on efficient and accurate localization,swarm systems perform tasks through formation control.This paper develops a clustering⁃based localization system,aiming at the large⁃scale and highly dynamic localization scenario under conditions of the global navigation satellite system(GNSS)⁃denied/restriction and non⁃line of sight(NLOS).The proposed system introduces the ranging timing optimization profile and the matrix completion optimization method.And it utilizes the Kalman filter algorithm to optimize the measurement error,thus the high⁃precision relative position estimation can be provided for each node with high robustness and flexibility.Finally,a set of hardware equipment is designed based on the ultra wideband(UWB),and the effectiveness of the proposed localization system is verified through field experiments and the accurate calibration methods.