Intelligent M-Robust Extended Kalman Filtering for Mobile Tracking

Abstract

This paper presents new M-estimation based robust extended Kalman filter (M-REKF) and fuzzy M-REKF (F-M-REKF) for mobile location estimation in smart urban macro-cells. Both filters can effectively counter the effects of non-Gaussian observation noises owing to the incorporation of measurement screening and enhanced robust regression. They can meet the FCC requirements and achieve satisfactory tracking performance. In general, the F-M-REKF performs better than the M-REKF due to fuzzy tuning of measurement noise covariances. Simulations demonstrate their advantages.