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Estimation of mobile station position and velocity in multipath wireless networks using the unscented particle filter

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4 Author(s)
Mohammed M. Olama ; Computational Sciences and Engineering Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, TN 37831, USA ; Seddik M. Djouadi ; Ioannis G. Papageorgiou ; Charalambos D. Charalambous

This paper presents a method based on wave scattering model for tracking a user. The 3D wave scattering multipath channel model of Aulin is employed together with particle filtering to obtain mobile station location and velocity estimates with high accuracy. This model takes into account non-line-of-sight and multipath propagation environments, which are usually encountered in wireless fading channels. The proposed estimation algorithms are based on the particle filter (PF) and the unscented particle filter (UPF). These algorithms cope with nonlinearities in the channel model in order to estimate the mobile location and velocity. They do not rely on linearized motion models, measurement relations, and Gaussian assumptions, in contrast to the extended Kalman filter (EKF). The performance of the PF/UPF approaches outperforms the EKF approach as simulation results indicate. Moreover, numerical results are presented to evaluate the performance of the proposed algorithms when measurement data do not correspond to the ones generated by the model. This shows the robustness of the algorithm.

Published in:

Decision and Control, 2007 46th IEEE Conference on

Date of Conference:

12-14 Dec. 2007