Vehicle velocity estimation based on Adaptive Kalman Filter

Abstract

Due to use sensors to measure V y and Vx are very expensive, it is necessary to estimate V y and Vx from other variables measured easily. A novel method based on Adaptive Kalman Filter (AKF) is proposed for estimation of V y and Vx in this paper by updating the mean and covariance of noise online. The estimation values are compared with simulator values from CarSim. The results demonstrate that the proposed method is robust and can improve the estimation accuracy of V y and Vx'