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Joint Time Synchronization and Localization of an Unknown Node in Wireless Sensor Networks

机译:无线传感器网络中未知节点的联合时间同步和本地化

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摘要

Time synchronization and localization are two important issues in wireless sensor networks. Although these two problems share many aspects in common, they are traditionally treated separately. In this paper, we present a unified framework to jointly solve time synchronization and localization problems at the same time. Furthermore, since the accuracy of synchronization and localization is very sensitive to the accuracy of anchor timings and locations, the joint time synchronization and localization problem with inaccurate anchors is also considered in this paper. For the case with accurate anchors, the joint maximum likelihood estimator and a more computationally efficient least squares (LS) estimator are proposed. When the anchor timings and locations are inaccurate, a generalized total least squares (GTLS) scheme is proposed. Crame????????r-Rao lower bounds (CRLBs) and the analytical mean square error (MSE) expressions of the LS based estimators are derived for both accurate and inaccurate anchor cases. Results show that the proposed joint estimators exhibit performances close to their respective CRLBs and outperform the separate time synchronization and localization approach. Furthermore, the derived analytical MSE expressions predict the performances of the proposed joint estimators very well.
机译:时间同步和本地化是无线传感器网络中的两个重要问题。尽管这两个问题有很多共同点,但传统上将它们分开对待。在本文中,我们提出了一个统一的框架,可以同时解决时间同步和本地化问题。此外,由于同步和定位的精度对锚定时间和定位的精度非常敏感,因此本文还考虑了锚定不准确的联合时间同步和定位问题。对于具有精确锚点的情况,提出了联合最大似然估计器和计算效率更高的最小二乘(LS)估计器。当锚定时和位置不正确时,提出了一种广义总最小二乘(GTLS)方案。基于LS的估计量的Crame r-Rao下界(CRLB)和分析均方误差(MSE)表达式是针对准确和不准确的锚点情况导出的。结果表明,所提出的联合估计量表现出接近其各自CRLB的性能,并且优于单独的时间同步和定位方法。此外,导出的MSE分析表达式很好地预测了所提出的联合估计量的性能。

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