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为解决无线传感器网络中节点自身定位问题,针对接收信号强度指示(received signal strength indication,RSSI)测距误差大和质心定位算法精度低的问题,提出一种基于最大似然估计的加权质心定位算法.首先通过计算将估计距离与实际距离之间的最大似然估计值作为权值,然后在权值模型中,引进一个参数k优化未知节点周围锚节点分布,最后计算出未知节点的位置并加以修正.仿真结果表明,基于最大似然估计的加权质心算法具有定位精度高和成本低的特点,优于基于距离倒数的质心加权和基于RSSI倒数的质心加权算法,适用于大面积的室内定位.
In order to solve the problem of localization of nodes in wireless sensor networks, a weighted centroid localization algorithm based on maximum likelihood estimation is proposed to solve the problem of large ranging error of received signal strength indication (RSSI) and low accuracy of centroid localization algorithm. Firstly, the maximum likelihood estimation between the estimated distance and the actual distance is taken as the weight. Then a parameter k is introduced into the weight model to optimize the distribution of anchor nodes around unknown nodes. Finally, the location of unknown nodes is calculated and corrected The simulation results show that the weighted centroid algorithm based on maximum likelihood estimation has the advantages of high positioning accuracy and low cost, which is superior to the centroid weighted algorithm based on distance reciprocal and centroid weighted algorithm based on RSSI reciprocal, which is suitable for large area indoor positioning.