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[1]马永涛,苗新龙,高政,等.无源标签多径环境下基于凸优化的定位算法[J].天津大学学报(自然科学版),2017,(09):953-960.[doi:10.11784/tdxbz201609014]
 Ma Yongtao,Miao Xinlong,Gao Zheng,et al.Localization Algorithm Based on Convex Relaxation in Passive Tag Multipath Environment[J].Journal of Tianjin University,2017,(09):953-960.[doi:10.11784/tdxbz201609014]
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无源标签多径环境下基于凸优化的定位算法()
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《天津大学学报(自然科学版)》[ISSN:0493-2137/CN:12-1127/N]

卷:
期数:
2017年09
页码:
953-960
栏目:
电气自动化与信息工程
出版日期:
2017-09-22

文章信息/Info

Title:
Localization Algorithm Based on Convex Relaxation in Passive Tag Multipath Environment
文章编号:
0493-2137(2017)09-0953-08
作者:
马永涛 苗新龙 高政 裴曙阳
天津大学微电子学院,天津 300072
Author(s):
Ma Yongtao Miao Xinlong Gao Zheng Pei Shuyang
School of Microelectronics, Tianjin University, Tianjin 300072, China
关键词:
无源标签 相位差欧氏距离 半定规划 二阶锥规划
Keywords:
passive tags phase difference Euclidean distance semi-definite programming(SDP) second-order cone programming(SOCP)
分类号:
TN911.7
DOI:
10.11784/tdxbz201609014
文献标志码:
A
摘要:
在室内无源超高频RFID定位中, 多径传播对定位结果的影响不可忽视.为了提高复杂多径环境下的定位精度, 提出了基于半定规划(SDP)和二阶锥规划(SOCP)的相位差欧式距离拟合定位算法.运用参考标签的位置信息, 对参考标签之间的理想相位差欧氏距离与实际距离进行拟合, 实现标签之间的距离估计.建立待定位标签与阅读器、参考标签距离估计模型, 将多径传播、高斯白噪声、相位差欧氏距离拟合引起的距离估计误差等效为正态分布, 利用参考标签的相位差信息和位置信息计算出正态分布参量.仿真结果表明, 提出的算法在最大多径数目为7时, 定位误差有90% 的概率低于2.3 m, 定位性能优于传统的基于测距的定位算法.
Abstract:
The effect of multipath propagation can’t be neglected when it comes to localization in indoor passive UHF RFID system. To improve the localization accuracy in dense multipath environment,the phase difference Euclidean distance fitting localization algorithms based on semi-definite programming(SDP)and second-order cone programming(SOCP)were proposed. The location information of reference tags was utilized to establish the relationship between ideal phase difference Euclidean distance and the real distance of reference tags. Therefore,the distance between tags could be estimated. The distance estimation model of tracking tags,readers and reference tags was established. Then,the effect of multipath propagation,Gauss white noise and the phase difference Euclidean distance fitting on distance estimation were modeled as normal distribution. Simulation results show that the localization error of the convex relaxation method is less than 2.3 m with the probability of 90% when the maximum number of multipath is 7,which outperforms the traditional range-based localization algorithms.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2016-09-06; 修回日期: 2016-12-05.
作者简介: 马永涛(1979—), 男, 博士, 副教授.
通讯作者: 马永涛, mayongtao@tju.edu.cn.
基金项目: 国家自然科学基金资助项目(61671318, 61401301); 天津市应用基础与前沿技术研究资助项目(15JCQNJC41900).
Supported by the National Natural Science Foundation of China(Nos.,61671318 and 61401301)and the Tianjin Research Program of Application Foundation and Advanced Technology(No.,15JCQNJC41900).
更新日期/Last Update: 2017-09-10