NLOS mitigation with biased Kalman filters for range estimation in UWB systems

In this paper, a non-line of sight (NLOS) error identification and mitigation technique utilizing modified biased Kalman filter in ultra-wideband (UWB) systems is proposed. NLOS error is considered one of the major error sources in range estimation and wireless location systems. To improve time-based location accuracy in UWB location systems, an NLOS identification and mitigation technique is derived. Kalman filters (KFs) are used for smoothing range data and mitigating the NLOS errors. We combine the modified biased Kalman filter and a sliding window to identify and mitigate different degree of NLOS errors. The simulation results show that the change of NLOS/LOS status can be identified accordingly and the NLOS errors can be mitigated effectively by modified biased Kalman filter. The technique achieves high accuracy in range estimation for UWB positioning and tracking.