接收信号强度指示测距模型修正与粒子群算法权重优化的节点定位算法  

Node Localization Algorithm Based on Received Signal Strength Indicator Ranging Model Modification and Particle Swarm Optimization Weight Optimization

作　　者：任克强[1] 温晓珍 REN Ke-qiang;WEN Xiao-zhen(School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China)

机构地区：[1]江西理工大学信息工程学院,赣州341000

出　　处：《科学技术与工程》2020年第31期12942-12947,共6页Science Technology and Engineering

基　　金：国家自然科学基金(61562038)。

摘　　要：为了降低接收信号强度指示(RSSI)测距误差对定位精度的影响,提出一种RSSI模型修正与粒群算法(PSO)权重优化相结合的定位算法。首先通过最小化误差平方和原则对RSSI测距模型参数进行校正,避免测距误差带入定位阶段,然后利用三边测量法进行粗略定位,得到未知节点的近似坐标,最后引入改进PSO算法对该近似坐标进行优化,在改进PSO算法中提出一种基于收敛因子的权重策略,有效地平衡了算法的搜索速度与搜索精度,从而得到节点坐标优化值。实验结果表明,该算法能够有效抑制测距误差积累,有更好的收敛性能和更高的全局优化能力,能实现更好的定位效果。To reduce the effect of received signal strength indicator(RSSI)ranging errors on localization accuracy,a localization algorithm combined of RSSI model correction and particle swarm optimization(PSO)weight localization was proposed.Firstly,parameters of the ranging model were corrected by the minimization of error square sum principle to avoid bringing errors into the localization stage.Then,approximate coordinates of the unknown nodes were obtained with results of broad localization from trilateral measurement.Finally,the improved PSO algorithm was introduced to optimize the approximate coordinates.In the improved PSO algorithm,a weight strategy based on convergence factor was used to effectively balance the search speed and search accuracy of the algorithm,so as to obtain the optimal values of node coordinates.The experimental results show that the algorithm can effectively suppress the accumulation of distance error.It can achieves better convergence,global optimization and node localization performance.

关 键 词：无线传感器网络 节点定位 接收信号强度指示 粒子群算法 非线性递减权重 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]