Nonparametric Bayesian Filtering for Location Estimation, Position Tracking, and Global Localization of Mobile Terminals in Outdoor Wireless Environments

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.

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