Paper
6 August 2003 Localization of DECT mobile phones based on a new nonlinear filtering technique
Andreas Rauh, Kai Briechle, Uwe D. Hanebeck, Clemens Hoffmann, Joachim Bamberger, Marian Grigoras
Author Affiliations +
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).
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andreas Rauh, Kai Briechle, Uwe D. Hanebeck, Clemens Hoffmann, Joachim Bamberger, and Marian Grigoras "Localization of DECT mobile phones based on a new nonlinear filtering technique", Proc. SPIE 5084, Location Services and Navigation Technologies, (6 August 2003); https://doi.org/10.1117/12.487800
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Nonlinear filtering

Transmitters

Stochastic processes

Motion models

Receivers

Filtering (signal processing)

Gaussian filters

Back to Top