Acta Metallurgica Sinica(English letters) ›› 2012, Vol. 19 ›› Issue (2): 22-29.doi: 10.1016/S1005-8885(11)60241-0

• Wireless • Previous Articles     Next Articles

NLOS error mitigation with information fusion algorithm for UWB ranging systems


  1. School of Control Science and Engineering, Shandong University, Jinan 250061, China
  • Received:2011-05-19 Revised:2011-12-21 Online:2012-04-30 Published:2012-04-17
  • Supported by:

    This work was supported by the National Natural Science Foundation for Distinguished Young Scholars of China (60825304), and the National Basic Research Development Program of China (2009cb320600).


This article puts forward a scalar weighting information fusion (IF) smoother with modified biased Kalman filter (BKF) and maximum likelihood estimation (MLE) to mitigate the ranging errors in ultra wide band (UWB) systems. The information fusion algorithm uses both the time of arrival (TOA) and received signal strength (RSS) measurement data to improve the ranging accuracy. At first, the ranging protocol of IEEE 802.15.4a acts as a multi-sensor system with multi-scale sampling. Then the scalar-based IF smoother accurately estimates the range measurement in the line of sight (LOS) and non-line of sight (NLOS) condition of UWB sensor network,during which the effectiveness of the IF in mitigating errors is especially focused during the LOS/NLOS transitions. Simulation results show that the proposed hybrid TOA-RSS fusion approach indicates a performance improvement compared with the usual TOA-only and other IF method, and the estimated ranging metrics can be used for achieving higher accuracy in location estimation and target tracking.

Key words:

NLOS error mitigation, biased Kalman filter, maximum likelihood estimation, information fusion, UWB ranging system