Nonlinear filter road vehicle model development

Abstract

This paper describes the first results of the investigation efforts performed in the development of the high-accuracy multisensor vehicle state estimation scheme. The use of UKF (Unscented Kalman Filter) in the state estimation scheme and vehicle model development framework is proposed. The first nonlinear vehicle model developed in this framework is also described. The model is able to cope with vehicle slip using multisensor data from inertial sensors, odometry, and the D-GPS. The simulation results indicated that the scheme is able to significantly reduce the errors in vehicle state estimates and is also able to perform real time internal sensors calibration.