Implications of Device Diversity for Organic Localization
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Author(s)
Park, Jun-geun
Curtis, Dorothy
Teller, Seth
Ledlie, Jonathan
Date Issued
April 2011
Journal
Proceedings of the 30th IEEE International Conference on Computer Communications (IEEE INFOCOM 2011)
Publisher
IEEE Communications Society
Citation
Park, Jun-geun et al. "Implications of Device Diversity for Organic Localization." in Proceedings of the 30th IEEE International Conference on Computer Communications (IEEE INFOCOM 2011), TS67:Localization, April 10-15, Shanghai, China.
Version
Author's final manuscript
Abstract
Many indoor localization methods are based on the
association of 802.11 wireless RF signals from wireless access
points (WAPs) with location labels. An “organic” RF positioning
system relies on regular users, not dedicated surveyors, to build
the map of RF fingerprints to location labels. However, signal
variation due to device heterogeneity may degrade localization
performance.
We analyze the diversity of those signal characteristics pertinent
to indoor localization — signal strength and AP detection
— as measured by a variety of 802.11 devices. We first analyze
signal strength diversity, and show that pairwise linear transformation
alone does not solve the problem. We propose kernel
estimation with a wide kernel width to reduce the difference
in probability estimates. We also investigate diversity in access
point detection. We demonstrate that localization performance
may degrade significantly when AP detection rate is used as a
feature for localization, and correlate the loss of performance
to a device dissimilarity measure captured by Kullback-Leibler
divergence. Based on this analysis, we show that using only signal
strength, without incorporating negative evidence, achieves good
localization performance when devices are heterogeneous.
Description
paper listed on conference site
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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