Abstract: An improved Kalman algorithm based on the “current” model was presented to avoid the influence of the acceleration limits. The difference between the velocity forecast estimate and the corrected velocity estimate was utilized to perform adaptive acceleration variance adjustment. The simulation of Kalman algorithms with different acceleration limit parameters proved that the performance of Kalman filter was influenced by the acceleration limits. In addition, the improved Kalman algorithm was compared with standard Kalman filter. The results showed that the proposed method forecast more accurately than the standard Kalman filter.

Key words: “current” model, Kalman filtering, adaptive adjust, state estimation