NLOS Identification and Ranging Error Mitigation for UWB Signal

Ultra-wideband(UWB) has achieved excellent application performance in many scenarios such as indoor positioning due to its strong penetration capability, multipath resistance and high positioning accuracy. For the problems such as large ranging errors of UWB in Non-Line-of-Sight(NLOS) environment, this paper firstly performs NLOS identification of UWB based on the position difference between first path(FP) and strongest path, the difference between received signal strength(RSS) and FP signal strength, and the distance residuals. Further, an NLOS error mitigation method with RSS and time of arrival fusion is proposed based on biased Kalman filtering(KF) and maximum likelihood estimation algorithm. Finally, experiments in dynamic and static scenarios are carried out to validate the proposed algorithm. The experimental results show that the identification accuracy of our method for NLOS is 95.42%. Under the static ranging scenario, our method improves 74.82% and 71.73% on average in the ranging accuracy compared with the original data and KF algorithm, respectively. In the dynamic positioning scenario, the average distance error of our method is 0.09 m, and it improves 62.5% in positioning accuracy compared to the original data and KF.