Non-line of Sight Error Mitigation in UWB Ranging Systems Using Information Fusion

Abstract

An information fusion(IF) smoother based on biased Kalman filtering(BKF) and maximum likelihood estimation(MLE) is proposed for ranging error mitigation with both time of arrival(TOA) and received signal strength(RSS) measurement data in IEEE 802.15.4a protocol to improve the ranging accuracy. In this study, the line of sight(LOS) and non-line of sight(NLOS) condition in ultra-wide band(UWB) sensor network is identified by a joint hypothesis test with residual variance of TOA measurement and maximum likelihood ratio of RSS measurement. Then an information fusion smoother is proposed to accurately estimate the ranging measurement corrupted by NLOS error. Simulation results show that proposed hybrid TOA-RSS information fusion approach indicates a performance improvement compared with the usual TOA-only method.