Abstract:

Obtaining vehicle velocity information accurately is of great importance to guarantee the safety when driving. In order to estimate the vehicle velocity, a velocity estimator was designed based on UKF(Unscented Kalman Filter) algorithm, and a comparision with the estimator based on KF(Kalman Filter) algorithm was made. Both the estimators took vehicle model with seven degrees of freedom as platform, and the models of UKF and KF algorithms were established in Matlab, then a comparative analysis experiment was done. The result shows that when the input produces mutations, the absolute error rate between UKF algorithm and
 real value is always less than 4 percent, the error rate dropped by 3 points compared to KF. The simulation result proves that UKF speed estimator can forecast vehicle velocity change tendency accurately, the performance is better than KF.

Key words: unscented Kalman filter (UKF) algorithm, Kalman filter (KF) algorithm, velocity estimation, absolute error