吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于RSSI极大似然估计定位算法的分析与实现

钟丽鸿, 胡成全, 金京姬   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2013-04-08 出版日期:2014-05-26 发布日期:2014-08-27
  • 通讯作者: 胡成全 E-mail:hucq@jlu.edu.cn

Analysis and Implementation of Maximum LikelihoodEstimation Positioning Algorithm Based on RSSI

ZHONG Lihong, HU Chengquan, JIN Jingji   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2013-04-08 Online:2014-05-26 Published:2014-08-27
  • Contact: HU Chengquan E-mail:hucq@jlu.edu.cn

摘要:

通过分析极大似然估计法进行求解方程未知节点位置可知, 代入最后一个方程锚节点(参照锚节点)的测距误差会对极大似然估计法定位误差产生较大影响, 并实现了基于RSSI的极大似然估计定位算法实测实验. 实验结果表明, 参照锚节点不带测距误差与参照锚节点带测距误差相比, 前者的定位误差小, 在30 m×30 m方形定位区
域内前者较后者平均定位误差值减小0.4~1.0 m.

关键词: 无线传感器网络, 定位, 极大似然估计法, 参照锚节点, 误差分析

Abstract:

When the maximum likelihood estimate equation was used to solve the unknown node’s position, it was found that the ranging error for the anchor node (reference node) in the last equation has greater impact on the localization error. The maximum likelihood experiment based on received signal strength indication in the reality shows that in the area of 30 m×30 m square positioning, average positioning error decreases from 0.4 m to 1.0 m when the reference node is being set without ranging error.

Key words: wireless sensor network (WSN), localization, maximum likelihood estimation algorithm, reference node, error analysis

中图分类号: 

  • TP393