An Adaptive Positioning Scheme Based on Radio Propagation Modeling for Indoor WLANs

This paper presents an adaptive location estimator based on radio propagation modeling and Kalman filtering for indoor wireless local area networks. In this positioning scheme, the location of a mobile terminal is extracted from the constant-velocity trajectory by linear equations and the radio propagation model by nonlinear equations. Results from simulation exhibit that the positioning error can be reduced with smaller sampling time of the Kalman filter. The simulation results also show that more than 95 percent of the estimated locations have error distances less than 1.55 meters.