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清华大学学报(自然科学版)  2015, Vol. 55 Issue (5): 514-519,525    
  电子工程 本期目录 | 过刊浏览 | 高级检索 |
基于多径指纹的概率匹配室内定位方法
李佳徽1, 张焱2, 栾凤宇1, 李雪茹1, 周来1, 周世东1
1. 清华大学 电子工程系, 北京 100084;
2. 北京理工大学 信息与电子学院, 北京 100081
Multipath-based probabilistic fingerprinting method for indoor positioning
LI Jiahui1, ZHANG Yan2, LUAN Fengyu1, LI Xueru1, ZHOU Lai1, ZHOU Shidong1
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;
2. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
全文: PDF(1723 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 空间交替广义期望最大化(SAGE)算法可以高效地实现室内信道多径参数的估计,同时提供相对较高的精度。该文提出一种基于多径指纹的概率匹配室内定位方法,将SAGE算法得到的信道多径参数作为指纹数据进行定位,以求获得更好的定位精度和鲁棒性。通过分析典型场景下的定位实验测量结果,并与同类型的传统室内定位方法进行比较,验证了该方法的有效性。
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李佳徽
张焱
栾凤宇
李雪茹
周来
周世东
关键词 信道多径估计指纹室内定位多径参数    
Abstract:The space-alternating generalized expectation-maximization (SAGE) algorithm provides efficient, accurate indoor channel multipath estimation. This paper describes a multipath-based probabilistic fingerprinting method for indoor positioning that utilizes the channel multipath parameters obtained by the SAGE algorithm as fingerprinting data to achieve better positioning accuracy and robustness. Tests of measurements in a typical indoor environment show that this method is more accurate than traditional indoor positioning methods.
Key wordschannel multipath estimation    fingerprinting    indoor positioning    multipath parameters
收稿日期: 2014-08-03      出版日期: 2015-08-04
ZTFLH:  TN929.5  
通讯作者: 周世东,教授,E-mail:zhousd@tsinghua.edu.cn     E-mail: zhousd@tsinghua.edu.cn
引用本文:   
李佳徽, 张焱, 栾凤宇, 李雪茹, 周来, 周世东. 基于多径指纹的概率匹配室内定位方法[J]. 清华大学学报(自然科学版), 2015, 55(5): 514-519,525.
LI Jiahui, ZHANG Yan, LUAN Fengyu, LI Xueru, ZHOU Lai, ZHOU Shidong. Multipath-based probabilistic fingerprinting method for indoor positioning. Journal of Tsinghua University(Science and Technology), 2015, 55(5): 514-519,525.
链接本文:  
http://jst.tsinghuajournals.com/CN/  或          http://jst.tsinghuajournals.com/CN/Y2015/V55/I5/514
  图1 定位流程图
  表1 指纹数据库结构
  图2 在线阶段多径传输示例
  图3 实验场景平面图
  表2 信道测量设备参数
  表3 不同多径数目性能比较
  图4 不同στ和σα 下MPFM 定位误差均值和标准差
  图5 不同στ和σα 下WMPFM 定位误差均值和标准差
  图6 MPFM 误差累计概率
  图7 WMPFM 误差累计概率
  图8 不同定位方法误差累计概率比较
  表4 不同定位算法性能比较
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