Mobile User Tracking Algorithm via Velocity Estimation for Microcellular Urban Environment

Abstract

A novel tracking algorithm for mobile user based on velocity estimation in microcellular urban environment is proposed in this paper. The Short-Time Fourier analysis of received signal strength is employed to estimate mobile speed. Utilizing user’s mobility model and a bank of extended Kalman filters, the algorithm tracks the mobile user by switching to the suitable extended Kalman filter based on the velocity and average received power estimates. The proposed tracking algorithm shows a good ability to predict user mobility behavior in urban area with multipath fading and shadowing phenomena.