Probabilistic radio-frequency fingerprinting and localization on the run

@article{Mirowski2014ProbabilisticRF,
  title={Probabilistic radio-frequency fingerprinting and localization on the run},
  author={Piotr W. Mirowski and Dimitris Milioris and Phil Whiting and Tin Kam Ho},
  journal={Bell Labs Technical Journal},
  year={2014},
  volume={18},
  pages={111-133}
}
Indoor localization is a key enabler for pervasive computing and network optimization. Wireless local area network (WLAN) positioning systems typically rely on fingerprints of received signal strength (RSS) measures from access points. In this paper, we review approaches for modeling full distributions of Wi-Fi signals, including Bayesian graphical models, smoothing, compressive sensing, and random field differentiation and concentrate on the Kullback-Leibler divergence metric that compares… CONTINUE READING
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