Joint Node Localization and Time-Varying Clock Synchronization in Wireless Sensor Networks
Joint Node Localization and Time-Varying Clock Synchronization in Wireless Sensor Networks
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DOI：
10.1109/twc.2013.090413.130324
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发表时间：
2013-05
影响因子：
10.4
通讯作者：
A. Ahmad;E. Serpedin;H. Nounou;M. Nounou
中科院分区：
文献类型：
--
作者：
A. Ahmad;E. Serpedin;H. Nounou;M. Nounou
从统计信号处理的角度来看，无线传感器网络中的节点定位和时钟同步问题自然是紧密相连的。在这项工作中，我们考虑通过结合节点振荡器缺陷的影响来联合估计未知节点的位置和时钟参数，这使得时钟参数具有时变性质。数据交换机制基于与锚节点的双向消息交换。为了减轻与最优最大后验估计器相关的计算复杂性，提出了两种迭代方法作为更简单的替代方案。第一种方法利用基于期望最大化（EM）的算法，该算法迭代地估计时钟参数和未知节点的位置。通过对数据进行非线性处理，使用最小二乘法 (LS) 获得位置估计问题的封闭式解，从而进一步简化 EM 算法。通过推导估计器均方误差 (MSE) 的混合 Cramer-Rao 下界 (HCRB) 来对估计算法的性能进行基准测试。理论研究结果得到了仿真研究的证实，仿真研究表明 LS 估计器与小到达时间测量噪声的 EM 算法的性能非常匹配，并且非常适合在低成本传感器网络中实现。
The problems of node localization and clock synchronization in wireless sensor networks are naturally tied from a statistical signal processing perspective. In this work, we consider the joint estimation of an unknown node's location and clock parameters by incorporating the effect of imperfections in node oscillators, which render a time varying nature to the clock parameters. The data exchange mechanism is based on a two-way message exchange with anchor nodes. In order to alleviate the computational complexity associated with the optimal maximum a-posteriori estimator, two iterative approaches are proposed as simpler alternatives. The first approach utilizes an Expectation-Maximization (EM) based algorithm which iteratively estimates the clock parameters and the location of the unknown node. The EM algorithm is further simplified by a non-linear processing of the data to obtain a closed form solution of the location estimation problem using least squares (LS). The performance of the estimation algorithms is benchmarked by deriving the Hybrid Cramer-Rao lower bound (HCRB) on the mean square error (MSE) of the estimators. The theoretical findings are corroborated by simulation studies which reveal that the LS estimator closely matches the performance of the EM algorithm for small time of arrival measurement noise, and is well suited for implementation in low cost sensor networks.