KL-divergence kernel regression for non-Gaussian fingerprint based localization

@article{Mirowski2011KLdivergenceKR,
  title={KL-divergence kernel regression for non-Gaussian fingerprint based localization},
  author={Piotr W. Mirowski and Harald Steck and Phil Whiting and Ravishankar Palaniappan and Michael MacDonald and Tin Kam Ho},
  journal={2011 International Conference on Indoor Positioning and Indoor Navigation},
  year={2011},
  pages={1-10}
}
Various methods have been developed for indoor localization using WLAN signals. Algorithms that fingerprint the Received Signal Strength Indication (RSSI) of WiFi for different locations can achieve tracking accuracies of the order of a few meters. RSSI fingerprinting suffers though from two main limitations: first, as the signal environment changes, so does the fingerprint database, which requires regular updates; second, it has been reported that, in practice, certain devices record more… CONTINUE READING
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