山东理工大学学报（自然科学版）Issue(3)：61-65,5.
一种基于泰勒级数多元变量展开模型定位算法
A localization algorithm based on Taylor series multivariable expansion model
摘要
Abstract
In order to improve positioning accuracy in wireless sensor networks ,a new Taylor se‐ries multivariable expansion localization model is established by the method of adding the dis‐tances information betw een unknow n nodes . In process of the algorithm solution , firstly the maximum likelihood estimation is utilized to obtain initial values of unknow n nodes . T hen ,its optimal values are calculated as the estimated location of unknown nodes by the weighted least squares method .To evaluate the performance of this algorithm ,simulations test the impact of different distance measurement error and the number of know n nodes on positioning error ,and the cumulative distribution function of algorithm .Simulation results show that the proposed al‐gorithm has achieved better performance on positioning accuracy and efficiency .关键词
泰勒级数多元变量展开/定位模型/最大似然估计/无线传感器网络Key words
Taylor series multivariable expansion/localization model/maximum likelihood esti-mation/wireless sensor networks分类
信息技术与安全科学引用本文复制引用
刘承鹏,夏斌,谢楠,彭荣群..一种基于泰勒级数多元变量展开模型定位算法[J].山东理工大学学报（自然科学版）,2016,(3):61-65,5.基金项目
山东省高校科技计划项目 （）
