›› 2014,Vol. 29 ›› Issue (4): 589-604.doi: 10.1007/s11390-014-1452-7

• Special Section on Selected Paper from NPC 2011 • 上一篇    下一篇

通信既众包:带有基于CSI测速功能的Wi-Fi室内定位系统

Zhi-Ping Jiang1 (蒋志平), Wei Xi1,* (惠维), Member, CCF, ACM, IEEE Xiangyang Li1,2 (李向阳), Senior Member, IEEE, Member, ACM, Shaojie Tang3 (唐少杰), Member, IEEE Ji-Zhong Zhao1 (赵季中), Member, CCF, ACM, IEEE, Jin-Song Han1 (韩劲松), Member, CCF, ACM, IEEE, Kun Zhao1 (赵鲲), Zhi Wang1 (王志), and Bo Xiao4 (肖波)   

  1. 1. School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710000, China;
    2. Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A.;
    3. Department of Information Science, University of Texas at Dallas, Richardson, TX, U.S.A.;
    4. Network Center, The Aviation University of Air Fone, Jinzhou 121000, China
  • 出版日期:2014-07-05 发布日期:2014-07-05
  • 作者简介:Zhi-Ping Jiang is a Ph.D candidate at Xi'an Jiaotong University, Xi'an. His research interests include localization, smart sensing, wireless communication, and image processing.
  • 基金资助:

    The work is supported by the National Natural Science Foundation of China under Grant Nos. 61325013, 61190112, 61170216, and 61228202, the Natural Science Foundation of USA under Grant Nos. CNS-0832120, CNS-1035894, ECCS-1247944, and ECCS-1343306, the Fundamental Research Funds for the Central Universities of China under Project No. 2012jdgz02 (Xi'an Jiaotong University), and the Research Fund for the Doctoral Program of Higher Education of China under Project No. 20130201120016.

Communicating Is Crowdsourcing:Wi-Fi Indoor Localization with CSI-Based Speed Estimation

Zhi-Ping Jiang1 (蒋志平), Wei Xi1,* (惠维), Member, CCF, ACM, IEEE Xiangyang Li1,2 (李向阳), Senior Member, IEEE, Member, ACM, Shaojie Tang3 (唐少杰), Member, IEEE Ji-Zhong Zhao1 (赵季中), Member, CCF, ACM, IEEE, Jin-Song Han1 (韩劲松), Member, CCF, ACM, IEEE, Kun Zhao1 (赵鲲), Zhi Wang1 (王志), and Bo Xiao4 (肖波)   

  1. 1. School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710000, China;
    2. Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A.;
    3. Department of Information Science, University of Texas at Dallas, Richardson, TX, U.S.A.;
    4. Network Center, The Aviation University of Air Fone, Jinzhou 121000, China
  • Online:2014-07-05 Published:2014-07-05
  • About author:Zhi-Ping Jiang is a Ph.D candidate at Xi'an Jiaotong University, Xi'an. His research interests include localization, smart sensing, wireless communication, and image processing.
  • Supported by:

    The work is supported by the National Natural Science Foundation of China under Grant Nos. 61325013, 61190112, 61170216, and 61228202, the Natural Science Foundation of USA under Grant Nos. CNS-0832120, CNS-1035894, ECCS-1247944, and ECCS-1343306, the Fundamental Research Funds for the Central Universities of China under Project No. 2012jdgz02 (Xi'an Jiaotong University), and the Research Fund for the Doctoral Program of Higher Education of China under Project No. 20130201120016.

近段时间众多室内定位方法与系统被提出用以实现基于位置的服务(LBS)的快速普及。其中,基于Wi-Fi指纹定位法是众多方法中最流行也相对最易部署的系统。指纹法的一个主要挑战就是如何降低指纹采集的复杂度与成本。近来研究领域提出通过众包的方法通过将大量用户采集的碎片数据整合自动构建指纹地图的思想,然而众包系统的低参与度的使这些方法无法迈向实用。在本文中,我们提出一种“基于CSI信息的被动式众包室内定位系统”C2IL。虽然采用众包思想,但本系统对于终端客户完全透明。系统的唯一要求仅是希望用户的移动设备连接到专用的802.11n AP上。C2IL提出一种创新的仅通过802.11n信道状态信息CSI即可对客户端准确测速的方法。在已知用户移动速度以及相邻AP信息时,我们使用图匹配方法从大量用户行走的数据中自动提取出Wi-Fi指纹以及指纹分布图。在定位阶段,我们设计了一种基于轨迹聚类的定位方法,它可以实现实时的室内定位与追踪。我们实现了C2IL并将它部署于一个真实的大型办公环境。广泛的评估显示测速系统误差在3%以内,而定位系统在复杂环境中80%时间内误差都小于2m。

Abstract: Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location-based service (LBS). Among them, Wi-Fi fingerprint-based approaches are the most popular solutions, and the core challenge is to lower the cost of fingerprint site-survey. One of the trends is to collect the piecewise data from clients and establish the radio map in crowdsourcing manner, however the low participation rate blocks the practical use.
In this work, we propose a passive crowdsourcing CSI-based Indoor Localization scheme, C2IL. Despite a crowdsourcing-based approach, our scheme is totally transparent to client except the only requirement is to connect to our 802.11n APs. C2IL is built upon an innovative method to accurately estimate the moving speed solely based on 802.11n Channel State Information (CSI). Knowing the walking speed of a client and its surrounding APs, a graph-matching algorithm is employed to extract the RSS fingerprints and establish the fingerprint map. In localization phase, we design a trajectory clustering-based localization algorithm to provide precise realtime indoor localization and tracking. We developed and deployed a practical working system of C2IL in a large office environment. Extensive evaluations indicate that the error of speed estimation is within 3%, and the localization error is within 2m at 80% time in very complex indoor environment.

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