稳态Kalman滤波器增益新算法

NEW ALGORITHMS OF STEAD STATE KALMAN FILTER GAIN

应用现代时间序列分析方法，基于ＡＲＭＡ新息模型，提出了稳态Ｋａｌｍａｎ滤波器增益的两种简单的新算法，并证明了它们的等价性．应用ＡＲＭＡ新息模型参数的递推辨识器伴随新算法，可实现自校正Ｋａｌｍａｎ滤波器．仿真例子说明了其有效性．

By using the modern time series analysis method and based on the ARMA innovation model,two new algorithms of steady state Kalman filter gain are presented,and their equivalence is proved.The self tuning Kalman filters can be implemented by using a recursive identifier of parameters for the ARMA innovation model,in conjunction with the new algorithms.A simulation example shows usefulness of the proposed algorithms.