Liu Yu
Autonomous Navigation and Microsystem Chongqing Key Laboratory，Chongqing University of Post and Telecommunications，Chongqing 400065, ChinaXie Yu
Autonomous Navigation and Microsystem Chongqing Key Laboratory，Chongqing University of Post and Telecommunications，Chongqing 400065, ChinaPeng Hui
Autonomous Navigation and Microsystem Chongqing Key Laboratory，Chongqing University of Post and Telecommunications，Chongqing 400065, ChinaZou Xinhai
Autonomous Navigation and Microsystem Chongqing Key Laboratory，Chongqing University of Post and Telecommunications，Chongqing 400065, ChinaLi Wangrun
Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem, Chongqing University of Post and Telecommunications, Chongqing 400065, ChinaZhao Bolong
Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem, Chongqing University of Post and Telecommunications, Chongqing 400065, China1. Autonomous Navigation and Microsystem Chongqing Key Laboratory，Chongqing University of Post and Telecommunications，Chongqing 400065, China;2. Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem, Chongqing University of Post and Telecommunications, Chongqing 400065, China
TP391
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 100m error is reduced to 0.33m.
