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Calibree: Calibration-Free Localization Using Relative Distance Estimations

  • Alex Varshavsky
  • Denis Pankratov
  • John Krumm
  • Eyal de Lara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5013)

Abstract

Existing localization algorithms, such as centroid or fingerprinting, compute the location of a mobile device based on measurements of signal strengths from radio base stations. Unfortunately, these algorithms require tedious and expensive off-line calibration in the target deployment area before they can be used for localization. In this paper, we present Calibree, a novel localization algorithm that does not require off-line calibration. The algorithm starts by computing relative distances between pairs of mobile phones based on signatures of their radio environment. It then combines these distances with the known locations of a small number of GPS-equipped phones to estimate absolute locations of all phones, effectively spreading location measurements from phones with GPS to those without. Our evaluation results show that Calibree performs better than the conventional centroid algorithm and only slightly worse than fingerprinting, without requiring off-line calibration. Moreover, when no phones report their absolute locations, Calibree can be used to estimate relative distances between phones.

Keywords

Mobile Phone Localization Algorithm Absolute Location Cell Tower Centroid Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alex Varshavsky
    • 1
  • Denis Pankratov
    • 1
  • John Krumm
    • 2
  • Eyal de Lara
    • 1
  1. 1.Department of Computer ScienceUniversity of TorontoCanada
  2. 2.Microsoft ResearchUSA

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