Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS 2011-01-0953
This paper presents an adaptive extended Kalman filter (EKF)-based sideslip angle estimator, which utilizes a sensor fusion concept that combines the high-rate inertial sensors measurements with the low-rate GPS velocity measurements. The sideslip angle estimation is based on a vehicle kinematic model relying on the lateral accelerometer and yaw rate gyro measurements. The vehicle velocity measurements from low-cost, single antenna GPS receiver are used for compensation of potentially large drift-like estimation errors caused by inertial sensors offsets. Adaptation of EKF state covariance matrix ensures a fast convergence of inertial sensors offsets estimates, and consequently a more accurate sideslip angle estimate. By using a detailed simulation analysis, it is found out that the main sources of estimation errors include inaccuracies of pre-estimated vehicle longitudinal velocity obtained from nondriven wheel speed sensors, the GPS velocity signal latency, and the road bank-related disturbances. Several compensation methods are proposed to suppress the influence of these errors.
Citation: Hrgetic, M., Deur, J., Pavkovic, D., and Barber, P., "Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS," SAE Int. J. Passeng. Cars – Mech. Syst. 4(1):700-712, 2011, https://doi.org/10.4271/2011-01-0953. Download Citation
Mario Hrgetic, Josko Deur, Danijel Pavkovic, Phil Barber
University of Zagreb, Jaguar Cars Limited
SAE 2011 World Congress & Exhibition
SAE International Journal of Passenger Cars - Mechanical Systems-V120-6, SAE International Journal of Passenger Cars - Mechanical Systems-V120-6EJ, Vehicle Dynamics Stability and Control, 2011-SP-2297