Abstract: This paper proposes a wireless sensor networks localization algorithm which is based on the weighted centroid RSSI and GASA optimization to improve the situation of node localization in wireless sensor network where the positioning error problems frequently occur. In order to locate the own position of unknown nodes, it is assumed that there is a certain proportion of the known position of the anchor nodes in wireless sensor networks. Since, the distance between unknown nodes and anchor nodes can be calculated out by RSSI weighted centroid algorithm, an unknown location parameter mathematical model can be established. Then, the most optimal solution to obtain a position of unknown nodes is achieved with the help of GASA optimization algorithm. The simulation results show that when the number of anchor nodes is 30, the average positioning error of this algorithm is fewer than 10%, which is lower than that of RSSI weighted centroid algorithm which is about 20%~25.5%. In addition, the more nodes are, the less positioning errors are.

Key words: wireless sensor networks, node localization, Received Signal Strength Indicator（RSSI） weighted centroid distance, Genetic Algorithm-Simulated Annealing（GASA） optimization algorithm

摘要： 针对无线传感器网络节点在自身定位中广泛存在较大的定位误差的问题，提出一种基于RSSI加权质心和GASA优化的无线传感器网络定位算法。该算法假设无线传感器网络中存在一定比例的位置已知的锚节点，利用RSSI加权质心算法计算未知节点与锚节点间的距离，建立以未知节点位置为参数的数学模型，用GASA优化算法计算最优解从而获得未知节点的位置，实现未知节点自身的定位。仿真实验的结果表明，当锚节点个数为30，算法的平均定位误差在10%以内，比RSSI加权质心算法降低了10%~15.5%左右，并且随着节点个数的增加平均定位误差降低。

关键词: 无线传感器网络, 节点定位, 接收的信号强度指示（RSSI）加权质心测距, 遗传模拟退火（GASA）优化算法