THE ADAPTIVE EXTENDED KALMAN FILTER ALGORITHM IN GPS POSITIONING FOR MOVING VEHICLES

摘要

In order to eliminate errors and improve the position precision of Global Position System (GPS), a new kinematical filtering method based on Kalman Filter and its algorithm is proposed. The algorithm considers different error sources as the total error of positioning results from the GPS receiver. The application of a "current statistical model " and an adaptive algorithm to estimate maneuvering vehicles, the acceleration variable of maneuvering vehicles can be equivalent to a sum composed of a current mean and a colored noise that conforms to one order Markov Process. And acceleration in each coordinate axis is considered as an instant current acceleration. An adaptive algorithm of acceleration mean is presented. The simulation result shows that the position precision has been improved after filtering.