Joint Access Point and User Localization Using Unlabeled WiFi RSS Data

Mahsa Shafiee and Richard Klukas

Abstract:	This paper investigates the problem of joint estimation of a pedestrian user path and the available WiFi access point locations. The observations are limited to unlabeled WiFi received signal strength (RSS) values. The problem is formed as a partially observable Markov decision process and RSS gradients are integrated to estimate and update the user locations along the path. The RSS data is modeled as a Gaussian process and gradient vectors are updated for each step based on the motion dynamics. Realistic assumptions and constraints are introduced to model the user’s movement and reduce the computational complexity.
Published in:	Proceedings of IEEE/ION PLANS 2016 April 11 - 14, 2016 Hyatt Regency Hotel Savannah, GA
Pages:	827 - 832
Cite this article:	Shafiee, Mahsa, Klukas, Richard, "Joint Access Point and User Localization Using Unlabeled WiFi RSS Data," Proceedings of IEEE/ION PLANS 2016, Savannah, GA, April 2016, pp. 827-832. https://doi.org/10.1109/PLANS.2016.7479778
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