电子学报 ›› 2018, Vol. 46 ›› Issue (6): 1351-1356.DOI: 10.3969/j.issn.0372-2112.2018.06.011

• 学术论文 • 上一篇    下一篇

面向WLAN室内定位的T检验样本容量优化方法

周牧, 卫亚聪, 田增山, 李玲霞   

  1. 重庆邮电大学移动通信重点实验室, 重庆 400065
  • 收稿日期:2017-01-06 修回日期:2017-06-05 出版日期:2018-06-25
    • 作者简介:
    • 周牧,男,1984年生于重庆.现为重庆邮电大学教授.主要研究方向为无线定位技术、机器学习与人工智能、凸优化理论.E-mail:zhoumu@cqupt.edu.cn;卫亚聪,女,1993年生于山西临汾.现为重庆邮电大学硕士生.主要研究方向为无线定位技术、数值计算.E-mail:2540462563@qq.com;田增山,男,1968年生于河南固始.现为重庆邮电大学教授、博士生导师.主要研究方向为蜂窝网无线定位系统、个人通信、GPS精密定位和姿态测量、数据压缩和数据融合.E-mail:tianzs@cqupt.edu.cn;李玲霞,女,1976年生于湖北.现为重庆邮电大学高级工程师,硕士生导师,主要研究方向为未来移动通信理论与技术、宽度无线接入技术.E-mail:lilx@cqupt.edu.cn
    • 基金资助:
    • 国家自然科学基金资助项目 (No.61301126,No.61471077); 长江学者和创新团队发展计划基金资助项目 (No.IRT1299); 重庆市科委重点实验室专项经费基金资助项目; 重庆市基础与前沿研究计划基金资助项目 (重点) (No.cstc2015jcyjBX0065); 重庆市高校优秀成果转化基金资助项目 (No.KJZH17117); 重庆市科委重点实验室专项经费,重庆邮电大学青年科学研究项目 (No.A2013-31)

T-test Based Sample Capacity Optimization for WLAN Indoor Localization

ZHOU Mu, WEI Ya-cong, TIAN Zeng-shan, LI Ling-xia   

  1. Chongqing Key Lab of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2017-01-06 Revised:2017-06-05 Online:2018-06-25 Published:2018-06-25
    • Supported by:
    • National Natural Science Foundation of China (No.61301126, No.61471077); Program supported by Changjiang Scholars and Innovative Research Team in University (No.IRT1299); Fund of Key Laboratory of Chongqing Municipal Science & Technology Commission; Key Program supported Chongqing Research Program of Basic and Frontier Technology (No.cstc2015jcyjBX0065); Supported by Excellent Achievements Transformation Fund of Chongqing University (No.KJZH17117); Fund of Key Laboratory of Chongqing Municipal Science & Technology Commission,  Youth Scientific Research Program of Chongqing University of Posts and Telecommunications (No.A2013-31)

摘要: WLAN(Wireless Local Area Networks)室内定位已受到人们广泛的关注,而在离线指纹采集阶段常常容易造成位置指纹RSS数据采集的盲目性和不可靠性,并忽略所需采集RSS(Received Signal Strength)样本容量与定位性能的关系.为了解决这一问题,本文提出一种面向WLAN室内定位的T检验样本容量优化方法.该方法在离线阶段利用OC(Operating Characteristics)函数优化指纹数据库允许的最小RSS样本容量,而在在线阶段利用T检验方法对目标终端进行粗定位,并进而提出基于T检验的KNN(K-Nearest Neighbour)算法以完成对目标终端的精定位.此方法用有限的样本容量获得较稳定的定位性能分析结果,显著地减少了大量的人力和时间开销.

关键词: 室内定位, 样本容量, T检验, OC函数, K近邻

Abstract: WLAN indoor localization has caught significantly wide attention.In offline phase,the location fingerprint RSS data acquisition often results in blindness and unreliability,and ignores the relations between the required RSS sample capacity and localization performance.To solve this problem,a new T-test based sample capacity optimization approach for WLAN indoor localization is proposed.In offline phase,the Operating Characteristics (OC) function is used to optimize the allowable minimum RSS sample capacity for the fingerprint database construction.In online phase,we perform the rough localization by using the T-test approach,and then propose the T-test based KNN algorithm for the fine localization of target terminal.This method uses a limited sample capacity to obtain a more stable localization performance analysis results,significantly reducing the amount of manpower and time overhead.

Key words: indoor localization, sample capacity, T-test, OC function, K-nearest neighbor

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