Vehicle Velocity Estimation Based on Adaptive Kalman Filter

摘要：

Due to use sensors to measure v, 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 V*.

关键词： vehicle dynamic model lateral velocity longitudinal velocity adaptive Kalma filter HSRItire model

作者: Liang Chu Yanru Shi Yongsheng Zhang Yang Ou Mingfa Xu

作者单位: Key Laboratory of Automobile Dynamic Simulation Jilin University Changchun, China College of Automotive Engineering, Jilin University Changchun, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 492-495

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）