GPS/TDOA Hybrid Location Algorithm Based on Federal Kalman Filter

Abstract

Generally, accuracy of GPS(Global Positioning System) is higher than that of cellular network. But in tall building urban area or indoor, relatively weak GPS signal makes the positioning unstable and inaccurate. TDOA(Time Difference of Arrival) is one of the most widely used positioning methods in cellular mobile communication systems, but its accuracy is not high enough to meet the growing demand. In urban where there are more base stations to support big communication capacity than in rural, the mobile terminal positioning accuracy and stability is relatively better. In order to make up for these inherent deficiency of GPS or TDOA separate positioning, this paper deduces a GPS/TDOA hybrid positioning algorithm based on federated kalman filter by giving error model, state equation and measurement equation of each local kalman filters. Simulation results show that the algorithm effectively improves the data fusion reliability and positioning accuracy.