Title :
Vehicle velocity estimation based on Adaptive Kalman Filter
Author :
Chu, Liang ; Shi, Yanru ; Zhang, Yongsheng ; Ou, Yang ; Xu, Mingfa
Author_Institution :
Key Lab. of Automobile Dynamic Simulation, Jilin Univ., Changchun, China
Abstract :
Due to use sensors to measure vy and vx are very expensive, it is necessary to estimate vy and vx from other variables measured easily. A novel method based on Adaptive Kalman Filter (AKF) is proposed for estimation of vy 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 vy and vx.
Keywords :
adaptive Kalman filters; covariance analysis; road vehicles; robust control; velocity control; CarSim; adaptive Kalman filter; noise covariance; robust method; vehicle velocity estimation; Estimation; Tires; HSRI tire model; adaptive Kalma filter; lateral velocity; longitudinal velocity; vehicle dynamic model;
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
DOI :
10.1109/CMCE.2010.5610261
