The node self-localization is an important application of wireless sensor networks. In order to enhance the localization accuracy , based on the centroid point of intersection algorithm which solution precision was superior to the classical least square algorithm, reference node was defined as the closest anchor node to the unknown node, the errors of RSSI measurement could be got by measuring the distance between the reference node and other anchor nodes, the effects of RSSI measurement error to the node localization precision could be suppressed effectively by correcting the distance between the unknown node and anchor nodes. Then improved the centroid point of intersection algorithm by introducing the ideological of quadrilateral localization algorithm and optimization of anchor nodes. The results of simulation achieved by MATLAB show that this algorithm has better location accuracy than the centroid point of intersection algorithm under the same environment.%节点自身定位是无线传感器网络的重要应用之一.为提高定位精度,以求解精度优于传统最小二乘法的交点质心算法为基础,定义距未知节点最近的锚节点为参考节点,通过测量参考节点与锚节点之间的距离获得RSSI的测距误差,并对未知节点与锚节点间的测量距离进行误差修正,抑制了RSSI测距误差对定位精度的影响；再引入四边测距定位和优选锚节点的思想,对算法进行改进.MATLAB仿真结果表明:本算法在相同实验环境下相较于交点质心法又进一步提高了定位精度.
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