You are facing the Mona Lisa: spot localization using PHY layer information

  • Authors:

  • Souvik Sen;Božidar Radunovic;Romit Roy Choudhury;Tom Minka

  • Affiliations:

  • Duke University, Durham, NC, USA;Microsoft Research, Cambridge, MA, USA;Duke University, Durham, NC, USA;Microsoft Research, Cambridge, United Kingdom

  • Venue:
  • Proceedings of the 10th international conference on Mobile systems, applications, and services
  • Year:
  • 2012

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Abstract

This paper explores the viability of precise indoor localization using physical layer information in WiFi systems. We find evidence that channel responses from multiple OFDM subcarriers can be a promising location signature. While these signatures certainly vary over time and environmental mobility, we notice that their core structure preserves certain properties that are amenable to localization. We attempt to harness these opportunities through a functional system called PinLoc, implemented on off-the-shelf Intel 5300 cards. We evaluate the system in a busy engineering building, a crowded student center, a cafeteria, and at the Duke University museum, and demonstrate localization accuracies in the granularity of 1m x 1m boxes, called "spots". Results from 100 spots show that PinLoc is able to localize users to the correct spot with 89% mean accuracy, while incurring less than 6% false positives. We believe this is an important step forward, compared to the best indoor localization schemes of today, such as Horus.