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Wireless Location Tracking Algorithms for Environments with Insufficient Signal Sources

机译:信号源不足的环境中的无线位置跟踪算法

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摘要

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 inapplicable for location tracking due to the deficiency of signal sources. In this paper, two predictive location tracking algorithms are proposed to alleviate this problem. The Predictive Location Tracking (PLT) scheme utilizes the predictive information obtained from the Kalman filter in order to provide the additional signal inputs for the location estimator. Furthermore, the Geometric-assisted PLT (GPLT) scheme incorporates the Geometric Dilution of Precision (GDOP) information into the algorithm design. Persistent accuracy for location tracking can be achieved by adopting the proposed GPLT scheme, especially with inadequate signal sources. Numerical results demonstrate that the GPLT algorithm can achieve better precision in comparison with other network-based location tracking schemes.
机译:近年来,对移动设备的位置估计和跟踪已引起了大量关注。基于网络的位置估计方案已经基于移动设备和基站之间的无线电信号被广泛采用。与卡尔曼滤波技术相关联的位置估计器被用于获取移动设备的位置估计和轨迹跟踪。然而,由于信号源的不足,大多数现有方案变得不适用于位置跟踪。本文提出了两种预测性位置跟踪算法来缓解这一问题。预测位置跟踪(PLT)方案利用从卡尔曼滤波器获得的预测信息,以便为位置估计器提供额外的信号输入。此外,几何辅助PLT(GPLT)方案将精度几何稀释(GDOP)信息纳入了算法设计。通过采用建议的GPLT方案可以实现持久的位置跟踪精度,尤其是在信号源不足的情况下。数值结果表明,与其他基于网络的位置跟踪方案相比,GPLT算法可以实现更高的精度。

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