TDoA based EKF localization for LTE

R. Sriram, D. Jalihal
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引用次数: 5

Abstract

The advent of location based services has increased the need for accurate positioning of mobile stations (MS). Global Positioning Systems (GPS) is not reliable in indoor and urban environments. Cellular wireless communication systems like the OFDM based 3GPP-LTE provide an alternative via Time Difference of Arrival (TDoA) measurements. Typical Extended Kalman Filter (EKF) algorithms using TDoA make certain assumptions about the mobility model and associated noise statistics of the MS. In this paper, we develop an alternate formulation of the TDoA localization problem and adaptive EKF algorithm that does not make the assumptions made by traditional EKF algorithms. We demonstrate that the proposed algorithm gives better position estimates than a static positioning estimator.
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基于TDoA的LTE EKF定位
基于位置的服务的出现增加了对移动站(MS)精确定位的需求。全球定位系统(GPS)在室内和城市环境中不可靠。蜂窝无线通信系统,如基于OFDM的3GPP-LTE,通过到达时间差(TDoA)测量提供了另一种选择。利用TDoA的典型扩展卡尔曼滤波(EKF)算法对ms的迁移模型和相关噪声统计进行了一定的假设。在本文中,我们提出了一种替代的TDoA定位问题和自适应EKF算法的表述,该算法不做传统EKF算法所做的假设。我们证明了该算法比静态定位估计器给出了更好的位置估计。
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