基于粒子群优化算法的WSN节点定位方法研究  

Research on Nodes Localization Method for Wireless Sensor Networks Based on Particle Swarm Optimization Algorithm

作　　者：林雯[1] 张烈平[2] 王守峰[2] 

机构地区：[1]广西工商职业技术学院,南宁530003 [2]桂林理工大学机械与控制工程学院,广西桂林541004

出　　处：《煤矿机械》2013年第5期84-86,共3页Coal Mine Machinery

基　　金：广西区自然科学基金项目(桂科自0991252);2012年度广西高等学校重点资助科研项目(桂教科研201202ZD051)

摘　　要：为提高无线传感器网络的节点定位精度,将惯性权重的粒子群优化算法应用到无线传感器网络节点定位中。定位方法以未知节点与其邻近锚节点之间的估计距离和测量距离的均方误差为适应度函数,采用基于惯性权重的粒子群优化算法对适应度函数进行优化,从而得到最优解,实现节点有效定位。仿真实验结果表明,与传统的最小二乘定位算法相比,基于惯性权重的粒子群优化算法的定位精度更高,稳定性更好,具有较好的定位效果。To improve the precision in location estimation, a nodes localization method ibr wireless sensor networks based on particle swarm optimization algorithm with self-adapting inertia was proposed in this paper. The sum of squared range errors between the unknown nodes and neighboring anchor nodes was considered as the objective function in this method. And the particle swarm optimization algorithm with self-adapting inertia was used to optimize the objective function, in order to obtain the optimal solution, and to achieve the effective nodes localization. The simulation experimental results showed that, compared with the east-squares method, the localization method base on particle swarm optimization algorithm with self-adapting inertia was stable with high localization accuracy and better localization effect.

关 键 词：无线传感器网络 粒子群优化算法 节点定位 最小二乘法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]