电力作业场景中一种高效的UWB和IMU融合定位算法

在电力作业场景等复杂环境中，超宽带（UWB）定位存在非直达情况（NLOS）性能下降严重的问题，利用UWB与惯性测量单元（IMU）融合可以改善定位精度，但IMU的测量存在误差累积，需要精确的UWB测量校正。对NLOS条件进行准确的鉴别和利用有助于定位精度的提升。提出一种基于扩展卡尔曼滤波（EKF）的UWB/IMU融合算法，利用电力作业场合中UWB测量分布性质来判定NLOS条件，并进行误差的缓解，有效提升NLOS条件下的定位精度。由于该算法不需要对环境有先验知识，也不需要进行IMU校正等操作，可用性较好。理论和实验结果表明，该算法的性能优于其他基线系统。

An Efficient Positioning Algorithm Based on UWB and IMU Fusion in Electric Power Operation Scenes

In complex environments such as electric power operation scenes, the performance of ultra wideband (UWB) positioning is seriously degraded due to non line of sight (NLOS) scenarios. The integration of UWB and inertial measurement unit (IMU) can improve the positioning accuracy, but there is error accumulation in IMU measurement, which requires accurate UWB measurement correction. Accurate identification and utilization of NLOS conditions is helpful to improve the positioning accuracy. In this paper, a UWB/IMU fusion algorithm based on extended Kalman filter (EKF) is proposed, which uses the distribution of UWB measurements in electric power operation scenes to determine NLOS conditions and mitigate errors, thus effectively improving the positioning accuracy under NLOS conditions. The proposed algorithm has good usability since it does not need prior knowledge of the environment and IMU correction. Theoretical and practical experimental results show that the performance of the proposed algorithm is superior to other baseline systems.