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

• Computer Networks and Distributed Systems • Previous Articles     Next Articles

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.

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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