面向相对导航的UWB测距误差估计与补偿方法

基于无人飞行器和智能机器人等载体构成的智能集群是当前的研究热点,相邻或相近集群成员之间精确的相对距离是密集集群实现协同控制的关键信息。超宽带(UWB)无线传输技术能传输信息,同时具有厘米级的理论测距精度,在集群的协同导航与控制中具有广阔的应用前景。面向集群成员间相对导航的厘米级测距需求,阐述了UWB的测距方案,分析了实际环境中UWB天线的时钟偏移、节点之间有相对速度和非视距环境引起的测距误差的特性,研究了UWB距离测量的状态检测和误差补偿、估计的方法,采用DW1000超宽带模块构建了实验环境,对所研究的方法进行实验验证。结果表明,所研究的方法可显著提高UWB在实际应用中的测距精度,与传统的测距算法相比,在空旷环境(LOS)状态下误差降低了70%,在非视距环境(NLOS)状态下误差降低了50%。

UWB ranging error estimation and compensation method for relative navigation

Intelligent swarm based on unmanned aerial vehicles or robots has become a research hotspot. To achieve collaborative control of dense cluster, the key information is to achieve the precise relative distance among adjacent agent clusters. Ultra wideband (UWB) wireless transmission technology can transmit information and realize centimeter level theoretical ranging accuracy. It has broad application prospect in coordinated navigation and control of clusters. In this paper, the UWB ranging scheme for centimeter level ranging requirement of relative navigation is first described. Then, the reason and characteristics of the ranging error caused by the clock offset of UWB antenna in the actual environment, the relative speed between the nodes and the non line of sight environment is analyzed. The state detection, error compensation and estimation methods of UWB distance measurement are studied. Finally, based on the DW1000 ultra wideband module, the experimental environment is constructed and the method studied in the paper is evaluated. Experimental results show that the error estimation and elimination method can significantly improve the accuracy of UWB in practical application. Compared with the traditional ranging algorithm, the ranging accuracy of the proposed method is improved under the relatively static scenario and a scene with relative speed between nodes. To be specific, the error is reduced by 70% in the line of sight environment state and by 50% in the non line of sight environment state.