Location tracking of mobiles: a smart filtering method and its use in practice

Accurate location tracking of mobile stations in cellular radio networks is of tremendous interest for many applications. In this work, we analyze the performance of a speed and location tracking algorithm using data from a field trial. The algorithm fits received signal strengths of surrounding base stations to corresponding predictions. These raw location estimates, in GSM available each 0.48 s, are subsequently smoothed by a model-based Kalman filter. An essential ingredient of our method is to find suitable initial parameters. The method is tested with measurement data from a field trial by Siemens. Although the field strength prediction method is rather simple, the location algorithm itself yields promising results. Typical average deviations from the true positions were 173.5 m for indoor, 117.7 m for walking, and 104.9 m for driving scenarios. This shows that the method is robust against moderate errors in the prediction model and leads to good results in a real GSM network.