研究目的
To present an automatic parameter setting method to achieve an accurate second-order Kalman ?lter tracker based on a steady-state performance index.
研究成果
The paper concludes that the proposed automatic parameter setting method for a Kalman ?lter tracker with the CV model assuming an arbitrary covariance matrix of process noise Q achieves more accurate tracking than conventional models with optimal settings. The proposed method has only one parameter, aD, corresponding to the target acceleration, and numerical analyses showed that the Q given by the proposed method can achieve more accurate tracking than conventional models with optimal settings.
研究不足
The proposed method is developed based on a 1D tracking model, and the consideration of more practical 2D and 3D tracking models is an important task for the future. Additionally, the interacting multiple model approach was not considered, which will be important in future work enabling the realization of more accurate tracking ?lters.
