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

机译:基于改进的Kalman滤波器的无线传感器网络的非视线节点跟踪算法

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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.
机译:跟踪移动节点对无线传感器网络引起了可观的研究兴趣。最具挑战性的问题是杂乱环境中的NLOS(非视线)问题,如室内。在本文中,我们提出了一种基于修改后的Kalman滤波器的非视线节点跟踪算法来减轻NLOS错误。首先用于估计移动节点的定位的最大似然方法。然后采用残余测试方法来消除较大的本地化误差。最后,我们通过改进的卡尔曼滤波器提高了跟踪精度。仿真结果表明,该算法可以拥有更高的跟踪精度并与现有经典方法相比,减轻了NLOS错误。

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