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Robust positioning system based on fingerprint approach

With growth of world wide cellular connections, localization within cellular network will play a central role in enabling value-added services. This is a huge revenue opportunity for mobile operators. Existing location techniques have poor performance in urban and indoor environments due to severe multipath and NLOS propagations, which are significant for those areas. Fingerprint-based methods have been preferred for those types of environments. In this work, a fingerprint-based technique is developed and applied. RSSI data used during training phase of the pattern-matching system are generated from the so-called in this work Thomas Kuerner propagation model. Moreover, motion detection algorithm and discrimination algorithm between indoor and outdoor environments are developed and could be used to further improve the positioning accuracy of a fingerprint-based positioning system. Tracking algorithm adapted to the fingerprint-based approach is developed and implemented. As result, a robust positioning system is achieved.