Calibree: Calibration-free Localization using Relative Distance Estimations

Alex Varshavsky, Denis Pankratov, John Krumm , Eyal de Lara

Sixth International Conference on Pervasive Computing (Pervasive), Sydney, Australia, May 2008



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 envi- ronment. 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 per- forms better than the conventional centroid algorithm and only slightly worse than fingerprinting, without requiring off-line calibration. More- over, when no phones report their absolute locations, Calibree can be used to estimate relative distances between phones.