Cellular Positioning by Database Comparison and Hidden Markov Models

Filtering of information with respect to position is believed to be an important factor in order to increase revenue of 2.5 and 3G cellular communication networks. We present a technique, which in conjunction with enhanced cell-id positioning methods has the potential to provide relatively inexpensive positioning with improved accuracy, wide coverage, and low system impact. The idea is to compare measurements of location sensitive parameters done by the receiver with a database. This process gives rise to primary position estimates, which is filtered by a secondary estimation procedure based on hidden Markov modeling. The position error is less than 24.1 meters 67% of the time and within 71.3 meters 95% of the time.

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