Scalar-weighted FastIMM Based on Fading Memory Filter Model and Adaptive Markov Transition Matrix

Abstract

In this study, a novel target tracking algorithm based on fading memory filter model and adaptive markov transition matrix is proposed to achieve a better tracking performance for the case where the measurement noise is high, target are distant and target maneuvers are intense. The proposed adp-FastSIMM-FM algorithm has been shown to have a better position estimation than the FastIMM-FM algorithm which has a better estimation than FastIMM and FastIMM-imp. Also, adp-FastSIMM-FM algorithm has a low computational cost.