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Position and Velocity Tracking in Cellular Networks Using Particle and Kalman Filtering with Comparison

机译:使用粒子和卡尔曼滤波的蜂窝网络位置和速度跟踪比较

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This paper presents two methods for tracking a user based on Aulin''s wave scattering channel model. The first method is based on the extended Kalman filter approach, while the second method is based on the particle filter approach. Aulin''s model takes into account non line of sight and multipath propagation environments, which are usually encountered in wireless fading channels. The received instantaneous electric field at the base station is a nonlinear function of the mobile location and velocity as Aulin''s model indicate. The proposed methods cope with nonlinearities in order to estimate the mobile location and velocity. The assumptions are knowledge of the channel and access to the instantaneous received field, which are obtained through channel sounding samples from the receiver circuitry. In contrast to the extended Kalman filter tracking approach, the particle filter approach does not rely on linearized motion models, measurement relations, and Gaussian assumptions. Numerical results are presented to evaluate the accuracy of the proposed methods
机译:本文提出了两种基于Aulin的波散射通道模型来跟踪用户的方法。第一种方法基于扩展的卡尔曼滤波方法,而第二种方法基于粒子滤波方法。 Aulin的模型考虑了通常在无线衰落信道中遇到的非视线和多径传播环境。正如Aulin模型所指出的,基站接收到的瞬时电场是移动位置和速度的非线性函数。所提出的方法应对非线性以估计移动位置和速度。这些假设是通道的知识以及对瞬时接收场的访问,这是通过从接收器电路获得的通道探测样本获得的。与扩展的卡尔曼滤波器跟踪方法相比,粒子滤波器方法不依赖于线性化运动模型,测量关系和高斯假设。数值结果表明了该方法的准确性。

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