Position and orientation estimation with high accuracy for a car-like vehicle

In this paper, position and orientation estimation with high accuracy based on GPS and encoders for a car-like vehicle is addressed. A novel architecture of position and orientation estimation is proposed, which consists of two extended Kalman filters (EKF) and a processing unit of Runga-Kutta-based dead reckoning. The first EKF fuses data from five encoders to estimate the velocity of vehicle and sideslip angle, The second EKF is applied to estimate position and orientation based on the measurement from precise GPS data and output from first EKF. To obtain better accuracy of estimation, an arbitrator is designed to switch on or off appropriate processing unit (EKF2 or dead reckoning). The results and analysis of experiments are presented to show the effectiveness of the proposed approach.