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Mobile device positioning using learning and cooperation

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5 Author(s)

We present a probabilistic graphical framework for mobile device positioning. We study the performance of a positioning algorithm, which implements the message-passing paradigm, in an indoor environment where a mobile device measures fingerprints of received signals. The key innovation in our approach is a stochastic parametric model for the fingerprint map that is adaptively tuned using on-line position estimates. The framework naturally extends to enable cooperative positioning in a network of mobile devices and we study the case of vehicle positioning as an illustration.

Published in:

Information Sciences and Systems (CISS), 2012 46th Annual Conference on

Date of Conference:

21-23 March 2012