Non-line of sight error mitigation in ultra-wideband ranging systems using biased Kalman filtering

In this paper, a non-line of sight (NLOS) errormitigation method based on biased Kalman filtering for ultra-wideband (UWB) ranging is proposed. The NLOS effect on the measures of signal arrival time is considered one of the major error sources in range estimation and time-based wireless location systems. An improved biased Kalman filtering system, incorporated with sliding-window data smoothing and hypothesis test, is used for NLOS identification and error mitigation. Based on the results of hypothesis test, the estimated ranges are either calculated by smoothing the measured range when line of sight (LOS) status is detected, or obtained by conducting error mitigation on the NLOS corrupted measured range when NLOS status is detected. The effectiveness of the proposed scheme in mitigating errors during the LOSto- NLOS and NLOS-to-LOS transitions is discussed. Improved NLOS identification and mitigation during the NLOS/LOS variations of channel status are attained by an adaptive variance-adjusting scheme in the biased filter. Simulation results show that the UWB channel status and the transition between NLOS and LOS can be identified promptly by the proposed scheme. The estimated time-based location metrics can be used for achieving higher accuracy in location estimation and target tracking.