电讯技术2017，Vol.57Issue(2)：139-144,6.DOI:10.3969/j.issn.1001-893x.2017.02.003
基于PSO-BP算法的无线传感器网络定位优化
Optimization of Wireless Sensor Network Positioning Based on PSO-BP Algorithm
摘要
Abstract
The existing localization algorithms are discussed. For the problem that received signal strength indication ( RSSI) based on the parameter model of positioning is easily affected by environment,a novel al―gorithm is proposed which combines particle swarm optimization ( PSO ) algorithm with back propagation ( BP) neural network. The correction of the weight of the BP network algorithm depends on the nonlinear gradient value. It is easy to form local extremum. At the same time,the number of learning is more. It should be optimized by PSO algorithm. In order to improve the positioning accuracy, the speed constant method is used to perform filtering. Then the initial weights and thresholds of the BP neural network is op―timized by the improved hybrid optimization algorithm. The performance of the algorithm is compared with that of the existing positioning algorithms. The number of hidden layer nodes varies from 12 to 19. The ex―perimental results show that the improved hybrid optimization algorithm can significantly improve the effect of ranging error on the positioning error compared with the general weighted algorithm and the traditional BP algorithm. The minimum positioning error can reach 0. 27 m in 25 m range.关键词
无线传感器网络/定位算法/测量误差/BP神经网络/粒子群优化/路径损耗模型Key words
wireless sensor network ( WSW )/localization algorithm/measurement error/back propagation ( BP) neural network/particle swarm optimization( PSO)/path loss model分类
信息技术与安全科学引用本文复制引用
卞国龙,黄海松,王安忆,于凯华..基于PSO-BP算法的无线传感器网络定位优化[J].电讯技术,2017,57(2):139-144,6.基金项目
贵州省科技支撑计划(黔科合 GZ 字[ 2015 ] 3034 ) （黔科合 GZ 字[ 2015 ] 3034 ）
国家自然科学基金资助项目( 51475097 ) （ 51475097 ）
国家科技支撑计划(2014BAH05F01) （2014BAH05F01）
贵州省科技基金项目(黔科合J字[2015]2043) （黔科合J字[2015]2043）
贵州省基础研究重大专项(黔科合JZ字[2014]2001) （黔科合JZ字[2014]2001）
