Adaptive EKF-Based Estimator of Sideslip Angle Using Fusion of Inertial Sensors and GPS

• Published in: SAE International Journal of Passenger Cars - Mechanical Systems 2011-04, Vol.4 (1), p.700-712, Article 2011-01-0953
• Main Authors: Hrgetic, Mario, Deur, Josko, Pavkovic, Danijel, Barber, Phil
• Format: Article
• Language: English
• ISSN: 1946-3995; 1946-4002; 1946-4002
• DOI: 10.4271/2011-01-0953

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.