Tracking Target with Constant Acceleration Motion Using Kalman Filtering

Maneuvering target tracking is recent hot topic in location based services. In this paper a kalman filtering based approach of mobile target tracking with constant acceleration motion, is presented to deal with uncertainties in measurement noises and abrupt changes in target velocity. Two algorithms namely, RSSI + kalman filter (KF) and RSSI + unscented kalman filter (UKF) are proposed to refine estimates of traditional RSSI based approach to obtain a smoothed target trajectory. The performance of the proposed algorithms are validated over simulated RSSIs and compared with traditional RSSI based approach in the context of tracking accuracy. The simulation results of proposed algorithms show the tracking accuracy of the order of centimeter scale, irrespective of dynamicity in RSSIs due hostile wireless environment.