Terrain/clutter based location prediction by using multi-condition Bayesian decision theory
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
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This paper investigates a Global Positioning system (GPS)-free positioning method for mobile units (MUs) in outdoor wireless environments by using the Bayesian filtering formulation. The procedure utilizes simulated inertial measurements, cell-ID of the serving base station, and pre-determined locations grouped according to cell antennas radio coverage in the experimentation area. The developed algorithm makes no assumptions on the initial position of the MU. However, the algorithm takes some time to converge. Experiments show the range of inertial measurement errors that would maintain reliable location information with accuracy comparable to GPS positioning.