Adaptive EKF-based estimator of sideslip angle using fusion of inertial sensors and GPS

Hrgetić, Mario and Deur, Joško and Pavković, Danijel and Barber, Phil (2011) Adaptive EKF-based estimator of sideslip angle using fusion of inertial sensors and GPS. = Adaptive EKF-based estimator of sideslip angle using fusion of inertial sensors and GPS. In: SAE 2011 International Congress and Exposition, 12-14.04.2011., Detroit, MI, United States.

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Abstract

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 lowcost, 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.

Item Type: Conference or Workshop Item (Lecture)
Keywords (Croatian): sideslip, estimation, GPS, inertial, sensor fussion, Kalman filter
Subjects: TECHNICAL SCIENCE > Electrical Engineering
Divisions: 900 Department of Robotics and Production System Automation > 910 Chair of Engineering Automation
Indexed in Web of Science: No
Indexed in Current Contents: No
Date Deposited: 01 Apr 2016 10:27
Last Modified: 13 Sep 2018 10:13
URI: http://repozitorij.fsb.hr/id/eprint/5364

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