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A Predictive Location Tracking Algorithm for Mobile Devices with Deficient Signal Sources

机译:具有缺陷信号源的移动设备预测位置跟踪算法

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location estimation and tracking for the mobile devices have attracted a significant amount of attention in recent years. The network-based location estimation schemes have been widely adopted based on the radio signals between the mobile device and the base stations. The location estimators associated with the Kalman filtering techniques are exploited to both acquire location estimation and trajectory tracking for the mobile devices. However, most of the existing schemes become unapplicable due to the insufficiency of signal sources. In this paper, a predictive location tracking (PLT) algorithm is proposed to alleviate this problem. The predictive information obtained from the Kalman filter is employed to provide the additional signal inputs for the location estimators. The proposed PLT scheme can offer persistent accuracy for location tracking of the mobile devices, especially with inadequate signal sources. Numerical results demonstrate that the proposed PLT algorithm can achieve better precision, comparing with other existing schemes, in mobile location estimation and tracking.
机译:移动设备的位置估计和跟踪近年来引起了大量的关注。已经基于移动设备和基站之间的无线电信号广泛采用基于网络的位置估计方案。与卡尔曼滤波技术相关联的位置估计被利用到移动设备的获取位置估计和轨迹跟踪。然而,由于信号来源的不足,大多数现有方案都变得不起起。本文提出了一种预测位置跟踪(PLT)算法来缓解这个问题。采用从卡尔曼滤波器获得的预测信息来提供用于位置估计器的附加信号输入。所提出的PLT方案可以为移动设备的位置跟踪提供持久的准确性,尤其是信号源不足。数值结果表明,所提出的PLT算法可以实现更好的精度,与其他现有方案相比,在移动位置估计和跟踪中。

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