计算机科学

计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 283-287.doi: 10.11896/jsjkx.210800270

• 计算机网络 • 上一篇    下一篇

基于M2M相遇区的PDR室内定位方法

唐清华1, 王玫1,2, 唐超尘1,3, 刘鑫1, 梁雯1   

  1. 1 桂林理工大学信息科学与工程学院 广西 桂林 541006
    2 桂林电子科技大学认知无线电与信息处理省部共建教育部重点实验室 广西 桂林 541004
    3 西安电子科技大学通信工程学院 西安 710071
  • 收稿日期:2021-08-31 修回日期:2022-01-27 出版日期:2022-09-15 发布日期:2022-09-09
  • 通讯作者: 唐超尘(2008046@glut.edu.cn)
  • 作者简介:(gxguilin@foxmail.com)
  • 基金资助:
    国家自然科学基金(62071135,61961010);广西重点研发计划(桂科AB17292058);广西科技基地和人才专项(桂科AD20159018);广西自然科学基金面上项目(2020GXNSFAA159004);认知无线电与信息处理省部共建教育部重点实验室主任基金(CRKL200104);广西高校无人机遥测重点实验室开放基金(WRJ2016KF01);广西高校中青年教师科研基础能力提升项目(2019KY1061)

PDR Indoor Positioning Method Based on M2M Encounter Region

TANG Qing-hua1, WANG Mei1,2, TANG Chao-chen1,3, LIU Xin1, LIANG Wen1   

  1. 1 School of Information Science and Engineering,Guilin University of Technology,Guilin,Guangxi 541006,China
    2 Provincial Ministry of Education Key Laboratory of Cognitive Radio and Signal Processing,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China
    3 School of Telecommunication Engineering,Xidian University,Xi'an 710071,China
  • Received:2021-08-31 Revised:2022-01-27 Online:2022-09-15 Published:2022-09-09
  • About author:TANG Qing-hua,born in 1981,master candidate,engineer.Her main research interests include location awareness and collaborative positioning.
    TANG Chao-chen,born in 1981,Ph.D candidate,lecturer.His main research interests include target detection and parameter estimation.
  • Supported by:
    National Natural Science Foundation of China(62071135,61961010),Guangxi Keypoint Research and Invention Program(GuiKe AB17292058),Project of Guangxi Technology Base and Talent Special Project(GuiKe AD20159018),Project of Guangxi Natural Science Foundation(2020GXNSFAA159004),Director Fund for Provincial Ministry of Education Key Laboratory of Cognitive Radio and Signal Processing(CRKL200104),Opening Project of Guangxi Key Laboratory of UAV Remote Sensing(WRJ2016KF01) and Project of Improving Research Ability for Guangxi Youth Teachers(2019KY1061).

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摘要： 在室内定位中,行人航迹推算(Pedestrian Dead Reckoning,PDR)的主要优点在于,其仅需要用户拥有智能手机就能实现定位,无须依赖外部环境,但是存在较大的累积误差,通常需要结合蓝牙、WiFi、地磁等技术融合定位来改善定位精度。此类方法需要架构一定的硬件节点且需要构建大量指纹数据库信息。针对该问题,提出了一种基于机器对机器(Machine to Machine,M2M)区域内纠正PDR的室内定位方法。该方法首先在行人行进过程中设置一个距离测量区域,其次在该区域内测量行人手机与其他手机的距离,最后通过三边定位方法进行定位,校正PDR的定位误差和精度。该方法不需要额外铺设其他硬件设施。实验结果表明,相比传统的PDR定位,该方法适合较长时间定位且平均定位误差降为0.36 m,具有较高的定位精度。

关键词: 行人航迹推算, 室内定位, 机器对机器, 三边定位, 粒子滤波

Abstract: In indoor positioning,the main advantage of pedestrian dead reckoning(PDR)is that the user only needs to have a smart phone to realize positioning,without relying on the external environment.However,there is a large cumulative error.Ge-nerally,it is necessary to combine Bluetooth,WiFi,geomagnetic or other technologies to improve the positioning accuracy.How-ever, this method requires some hardware nodes and a fingerprint database to be built for this purpose.To solve this problem,an indoor positioning method based on correcting PDR in machine to machine(M2M)area is proposed.Firstly,a distance measurement area is set up during pedestrian travel.Secondly,the distance between pedestrian mobile phones and other mobile phones is measured in this region.Finally,the positioning error and accuracy of PDR are corrected by trilateral positioning method.The method has the advantages that no additional hardware facilities are required.Experimental results show that,compared with the traditional PDR positioning,this method is suitable for long-time positioning,and the average positioning error is reduced to 0.36 m,with high positioning accuracy.

Key words: Pedestrian dead reckoning, Indoor positioning, Machine to machine, Trilateral positioning, Particle filtering

中图分类号: 

  • TP312
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