Push the limit of WiFi based localization for smartphones

Hongbo Liu, Yu Gan, Jie Yang, Simon Sidhom, Yan Wang, Yingying Chen, Fan Ye

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

348 Scopus citations

Abstract

Highly accurate indoor localization of smartphones is critical to enable novel location based features for users and businesses. In this paper, we first conduct an empirical investigation of the suitability of WiFi localization for this purpose. We find that although reasonable accuracy can be achieved, significant errors (e.g., 6 ~ 8m) always exist. The root cause is the existence of distinct locations with similar signatures, which is a fundamental limit of pure WiFibased methods. Inspired by high densities of smartphones in public spaces, we propose a peer assisted localization approach to eliminate such large errors. It obtains accurate acoustic ranging estimates among peer phones, then maps their locations jointly against WiFi signature map subjecting to ranging constraints. We devise techniques for fast acoustic ranging among multiple phones and build a prototype. Experiments show that it can reduce the maximum and 80-percentile errors to as small as 2m and 1m, in time no longer than the original WiFi scanning, with negligible impact on battery lifetime.

Original languageEnglish
Title of host publicationMobiCom'12 - Proceedings of the 18th Annual International Conference on Mobile Computing and Networking
Pages305-316
Number of pages12
DOIs
StatePublished - 2012
Event18th Annual International Conference on Mobile Computing and Networking, MobiCom 2012 - Istanbul, Turkey
Duration: 22 Aug 201226 Aug 2012

Publication series

NameProceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM

Conference

Conference18th Annual International Conference on Mobile Computing and Networking, MobiCom 2012
Country/TerritoryTurkey
CityIstanbul
Period22/08/1226/08/12

Keywords

  • Peer assisted localization
  • Smartphone
  • WiFi fingerprint localization

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