Non-line of sight node tracking algorithm based on modified Kalman filter for wireless sensor networks

Tracking of the mobile node has attracted considerable research interest for wireless sensor networks. The most challenging issue is NLOS (non-line of sight) problem in cluttered environments such as indoor. In this paper, we propose a Non-Line of Sight Node tracking algorithm based on modified Kalman filter to mitigate the NLOS error. The maximum likelihood method is firstly used to estimate the localization of the mobile node. Then the residual test method is employed to remove the larger localization error. Finally, we improve the tracking accuracy by the modified Kalman filter. Simulation results show that the proposed algorithm could own higher tracking accuracy and mitigate the NLOS error in comparison with existing classical methods.

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