Abstract: In wireless sensor networks lakes monitoring, the node location which randomly drifts in a certain range, makes location accuracy need to amend and improve. Minimum Error of Secondary Localization Estimation algorithm（MESLE） is proposed in this paper, initially, two groups of three beacon nodes are placed at two sides of the network, and trilateration method is used to locate the unknown node, the central point is calculated through the analysis of RSSI ranging error, and then it sets up two groups of measuring coordinate to location correction, finally weighted estimates the two sets of coordinate measuring results with the help of hop distance to obtain the optimized minimum error of node localization. It is shown that MESLE can effectively reduce the positioning error in lakes monitoring compared to the conventional trilateration method and FTL algorithm through the simulation.

Key words: minimum error, weighted estimate, trilateration, FTL algorithm

摘要： 无线传感网湖泊监测中，节点位置在一定范围内随机漂移，导致定位精度需持续修正并提高精度。提出最小误差二次定位估计算法，初始时在网络中设定两组配置有GPS的3个信标节点，利用三边测量法对未知节点进行定位，通过分析RSSI测距误差求出中心点，建立两组测量坐标进行定位修正，再使用跳距对两组坐标测量结果进行加权估计，获得优化后的最小误差节点定位。对比常规的三边测量法和FTL算法，通过仿真验证，该算法在湖泊监测中能有效地减小定位误差。

关键词: 最小误差, 加权估计, 三边测量法, FTL算法