基于UWB/PDR的航向发散自适应修正算法研究

Research on adaptive correction algorithm of heading divergence based on UWB/PDR

为解决航位推算(PDR)算法累积误差过大并且长航时航向发散的问题,提出了一种基于UWB/PDR自适应扩展卡尔曼滤波(EKF)融合算法。该算法通过UWB定位值和PDR实时解算位置得到自适应校准因子,通过在常规的EKF算法的基础上增加自适应校准因子动态调整UWB观测值的权重来校准位置误差。并用UWB的实时测距对PDR的航向发散进行周期性修正。实验结果表明,自适应EKF融合算法相较于纯PDR航向发散误差降低了63.9%,相较于标准EKF融合算法发散误差降低了31.1%,同时定位百米误差降至0.33 m。

To solve the problem of excessive cumulative error and long heading divergence in the position projection(PDR)algorithm,an adaptive extended Kalman filter(EKF)fusion algorithm based on UWB/PDR is proposed.The adaptive calibration factor can be achieved from the UWB positioning value and the PDR real-time position solution,and the position error is calibrated by dynamically adjusting the weight of the UWB observation with the adaptive calibration factor based on the conventional EKF algorithm.And the real-time ranging of the UWB is used to periodically correct the heading divergence of the PDR.The experimental results show the heading dispersion error is reduced by 63.9%with the adaptive EKF fusion algorithm compared to the pure PDR and 31.1%compared to the general EKF fusion algorithm,Moreover,the positioning 100 m error is reduced to 0.33 m.