Mobile Station Tracking in Multipath Wireless Networks Using Ensemble Square Root Filter

Advances in Computing and Communications（2014）

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摘要

In this work, we explore the possibility of applying an Ensemble square root filter (EnSRF) for tracking mobile stations in multi-path wireless networks. The EnSRF applied here is a variant of the Ensemble Kalman filter, that makes use of the Kalman update formulas within a Monte Carlo setup for estimating the unknown state (position) of the mobile stations. Multipath propagation environments encountered in wireless fading channels are modelled fairly well by the Aulins3-D scattering measurement model adopted here. The results obtained via EnSRF shows an improvement in convergence and accuracy of the position estimates over those obtained with some of the conventional particle filters commonly used in such nonlinear environments.

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关键词

kalman filters,monte carlo methods,channel estimation,convergence,fading channels,mobile radio,multipath channels,radio tracking,aulins 3-d scattering measurement model,ensrf,ensemble kalman filter,monte carlo setup,convergence improvement,ensemble square root filter,mobile station tracking,multipath propagation environments,multipath wireless networks,nonlinear environments,position estimation accuracy,unknown state estimation,wireless fading channels

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