中文摘要：

针对无线传感器网络空间定位问题进行了研究。为了提高未知节点的定位精度,提出一种基于鸡群优化的无线传感器网络三面定位算法。该算法结合了两种未知节点的求解方法,首先利用三面定位模型,通过求取三个面的交点来获取未知节点的坐标;再使用鸡群优化算法进行改进,根据三面定位法计算出的坐标值以及离未知节点最近的信标节点的坐标进行初始化,迭代寻优。使用MATLAB进行仿真,改变算法的迭代次数、信标节点占比和通信距离来对定位精度进行分析。结果表明该定位算法具有较高的定位精度与较快的收敛速度,且陷入局部最优的可能性低于粒子群定位算法。

英文摘要：

In order to improve the localization accuracy of unknown nodes in three dimension wireless sensor network, this paper proposed the three surfaces localization algorithm （ TSLA ） based on chicken swarm optimization for wireless sensor net- work. This algorithm combined two methods. Firstly, it using through TSLA model calculated the intersection point of three surfaces to obtain the coordinates of the unknown node. Then it used chicken swarm optimization to find more accurate coordinates,which initialized the node calculated by TSLA and the nearest beacon node. In the end, it made the MATLAB simula- tion by changing numbers of iterations, the proportion of beacon nodes and the communication distance to analyze the location accuracy. Simulation results show that this algorithm has more accurate localization accuracy, faster convergence speed and lower probability of local optimum than particle swarm optimization localization algorithm.