基于差分演化的无线传感器网络节点定位

针对无线传感器网络（WSN）节点的定位问题，提出一种基于差分演化的WSN节点定位算法。根据相邻节点间估计距离和测量距离之间的偏差构造目标函数，利用差分演化算法求出函数的最优解，达到最优解时的节点坐标即为未知节点的估计坐标。实验结果表明，该算法在锚节点比例为10％，节点无线通信半径R为1．8r的情况下，平均定位误差不超过5％，与带梯度搜索的半定规划定位算法相比，其定位精度更高。

Wireless Sensor Network Node Localization Based on Differential Evolution

This paper proposes a node localization algorithm for Wireless Sensor Network（WSN） based on Differential Evolution（DE）. The proposed algorithm constructs objective function according to the error of estimated distance from measured distance between neighboring nodes, and uses DE algorithm to find optimal solutions to the objective function. When the algorithm finds optimal solutions, it gets the estimated coordinates of unknown nodes. Experimental result shows that the localization accuracy of the proposed algorithm is less than 5% when the percentage of anchor nodes is 10% and the transmission range R of nodes is l.Sr, and the proposed algorithm can achieve higher localization accuracy than Semi-definite Programming（SDP） with gradient search localization algorithm.