Particle Filtering of Database assisted Positioning Estimates using a novel Similarity Measure for GSM Signal Power Level Measurements

In this paper we present a novel and statistically motivated similarity measure for database assisted positioning of GSM mobile terminals by evaluating signal power level reports which are transmitted regulary. Unlike a simple Euclidian distance measure, the proposed scheme incorporates inherent information about signal power level measurements requested by the serving base station but not reported by the mobile terminal. Furthermore we show how the Monte Carlo method of nonlinear post filtering using particle filtering helps to obtain better position estimates and surprisingly also helps to reduce the computational complexity. Results are presented for real field data.