Nonparametric Bayesian filtering for location estimation, position tracking, and global localization of mobile terminals in outdoor wireless environments

Authors:
Mohamed Khalaf-Allah
Affiliations:
Institute of Communications Engineering, Faculty of Electrical Engineering and Information Technology, Leibniz University of Hannover, Hannover, Germany
Venue:
EURASIP Journal on Advances in Signal Processing
Year:
2008

Citing 3
Cited 0

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Wireless information networks
Mobile Location in GSM Networks using Database Correlation with Bayesian Estimation

ISCC '06 Proceedings of the 11th IEEE Symposium on Computers and Communications
Prediction of outdoor and outdoor-to-indoor coverage in urban areas at 1.8 GHz

IEEE Journal on Selected Areas in Communications

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Abstract

The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data. Location estimation refers to the mobile positioning problem when both the initial location and motion measurement data are not available. If both are available, the positioning problem is referred to as position tracking. When only motion measurements are available, the problem is known as global localization. These positioning problems were solved within the Bayesian filtering framework. Filter derivation and implementation algorithms are provided with emphasis on the mapping approach. The radio maps of the experimental area have been created by a 3D deterministic radio propagation tool with a grid resolution of 5 m. Real-world experimentation was conducted in a GSM network deployed in a semiurban environment in order to investigate the performance of the different positioning algorithms.