摘要
应用白噪声估计理论和现代时间序列分析方法，对于带相关噪声和观测时滞系统，基于ＡＲＭＡ新息模型提出了一种稳态Ｋａｌｍａｎ估值器，可统一处理滤波、平滑和预报问题，且具有渐近稳定性避免了解Ｒｉｃｃａｔｉ方程。
Using white noise estimation theory and modern time series analysis method, this paper presents a steady state Kalman estimators based on the ARMA innovation model for systems with correlation noises and measurement delay,which can handle the filtering,smoothing and prediction problems in a unified framework,and can be applied in real time.A simulation example shows usefulness of the proposed estimators.
出处
《信息与控制》
CSCD
北大核心
1999年第4期249-254,共6页
Information and Control
基金
国家自然科学基金
关键词
KALMAN估值器
滤波
平滑
预报
离散系统
steady state Kalman estimators,filtering,smoothing,prediction,unified algorithm
