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Proceedings Paper

Localization of DECT mobile phones based on a new nonlinear filtering technique
Author(s): Andreas Rauh; Kai Briechle; Uwe D. Hanebeck; Clemens Hoffmann; Joachim Bamberger; Marian Grigoras
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Paper Abstract

In this paper, nonlinear Bayesian filtering techniques are applied to the localization of mobile radio communication devices. The application of this approach is demonstrated for the localization of DECT mobile telephones in a scenario with several base stations and a mobile handset. The received signal power, measured by the mobile handsets, is related to their position by nonlinear measurement equations. These consist of a deterministic part, modeling the received signal power as a function of the position, and a stochastic part, describing model errors and measurement noise. Additionally, user models are considered, which express knowledge about the motion of the user of the handset. The new Prior Density Splitting Mixture Estimator (PDSME), a Gaussian mixture filtering algorithm, significantly improves the localization quality compared to standard filtering techniques as the Extended Kalman Filter (EKF).

Paper Details

Date Published: 6 August 2003
PDF: 12 pages
Proc. SPIE 5084, Location Services and Navigation Technologies, (6 August 2003); doi: 10.1117/12.487800
Show Author Affiliations
Andreas Rauh, Univ. Ulm (Germany)
Kai Briechle, Technische Univ. Muenchen (Germany)
Uwe D. Hanebeck, Univ. Karlsruhe (Germany)
Clemens Hoffmann, Siemens AG (Germany)
Joachim Bamberger, Siemens AG (Germany)
Marian Grigoras, Siemens AG (Germany)

Published in SPIE Proceedings Vol. 5084:
Location Services and Navigation Technologies
Yilin Zhao, Editor(s)

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