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Relative Location Estimation Algorithm Based on Coordinates Inner Product Matrix-Based Maximum Likelihood

机译:基于坐标内积矩阵最大似然的相对位置估计算法

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摘要

We present a relative location estimation algorithm based on the coordinates inner product matrix-based maximum likelihood (CML) for determining the relative locations of sensor nodes in wireless sensor networks. We use the geodesic distance between each node to obtain the coordinates inner product matrix, then derive the maximum-likelihood estimator for coordinates inner product matrix to estimate the coordinates of sensor nodes. The simulation results show that the proposed algorithm outperforms existing solutions in terms of the location accuracy in wireless sensor networks.
机译:我们提出了一种基于坐标内积矩阵的最大似然(CML)的相对位置估计算法,用于确定无线传感器网络中传感器节点的相对位置。我们使用每个节点之间的测地距离获得坐标内积矩阵,然后导出坐标内积矩阵的最大似然估计器以估计传感器节点的坐标。仿真结果表明,该算法在无线传感器网络中的定位精度方面优于现有解决方案。

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