基于测距和灰狼优化的无线传感器网络定位算法

节点定位是无线传感器网络实际应用中的关键问题，为了提高定位精度，提出了一种基于测距和改进灰狼优化的无线传感器网络定位算法。本文提出了一种用三个信标节点坐标估计未知节点坐标的定位数学模型，通过该模型完成未知节点初步定位估计，将其作为基于对数递减策略的灰狼优化算法的初始值，通过改进灰狼优化算法寻优获取未知节点的优化坐标。仿真结果显示：通过与已有相关定位算法相比较，本文所提出的算法定位精度更高，并且具有对测距误差鲁棒性强的优点。

Sensor Node Localization Based on RSSI Ranging and Grey Wolf Optimizer Algorism in wireless sensor network

Node localization is a key problem in the practical application of wireless sensor network. In order to improve the localization accuracy, a node location algorithm based on RSSI and the improved gray wolf optimization (GWO) algorithm is proposed. A localization mathematical model is designed .The model is used to calculate the estimated coordinates of unknown nodes, and the calculated node coordinate is taken as the initial position of the logarithmic decrement strategy GWO (LOGGWO)algorithm .The LOGGWO is employed to optimize the coordinates of unknown nodes. The simulation results show that the proposed algorithm has higher localization accuracy and has strong robustness to range error in comparison with other localization algorithms.