GPS Based Estimation of Vehicle Sideslip Angle Using Multi-Rate Kalman Filter with Prediction of Course Angle Measurement Residual

摘要

In this paper, a new vehicle sideslip angle estimation based on GPS is proposed. Course angle obtained from GPS receiver can be utilized as one measurement for estimation design, together with the yaw rate from gyroscope. While yaw rate is sampled every 1 ms, the sampling time of course angle is much longer (200 ms). During inter-samples (between two updates of course angle), the conventional estimation method relies upon only yaw rate measurement. In order to enhance the estimation accuracy, multi-rate Kalman filter with the prediction of course angle measurement residual during inter-samples is designed. Experiments are conducted to verify the effectiveness of the proposed algorithm.