A novel angle-of-arrival assisted extended Kalman filter tracking algorithm with space-time correlation based motion parameters estimation

In this paper, we propose a novel mobile terminal (MT) tracking approach performed at the fixed terminal (FT). The method involves three steps: motion-dependent parameters estimation, extended Kalman filter (EKF) based tracking and enhanced estimation accuracy through additional partial location information. An algorithm based on the space-time correlation of the received signal is first proposed to estimate the radial velocity (both speed and direction) of the MT. The EKF-based tracking is next adopted to estimate the current location of the MT by using the estimated parameters and the previous location estimate. Finally, additional high-resolution angle-of-arrival (HR-AoA) estimate is applied and we show how this partial location information can be fused with the tracking results to further improve the tracking accuracy. The performances of the algorithms are studied through simulations.