An Improved Federal Kalman Filter Based on Smoother for Wireless Localization

Abstract

Federal Kalman filter is often used in multi-sensor wireless localization system. In this paper, we estimate the target location in non line of sight (NLOS) propagation. An approach based on federal Kalman filter is proposed, which is called smooth-federal Kalman filter. Federal Kalman filter uses standard Kalman filter in local filter to processes data in a forward recursion. Kalman smoother which processes data in a backward recursion is addressed in ordinary federal Kalman filter. Simulation and comparison results show that the estimation of the proposed approach performs superior to federal Kalman filter in NLOS propagation.