广义系统分离随机偏差两段解耦Wiener滤波器

Separate stochastic bias two-stage decoupled Wiener filters for descriptor systems

应用现代时间序列分析方法，基于ＡＲＭＡ新息模型和白噪声估值ｇ，提出了广义系统分离随机偏差两段解耦Ｗｉｅｎｅｒ滤波器，可统一处理滤波、平滑和预报问题，且具有渐近穗定性和最优性．仿真例子说明了其有效性。

Using modern time-series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimators, two -stage decoupled Wiener filters are pres- ented or descriptor systems with stochastic bias. They can hand1e the filtering, smoothing and predic- tion problems in a united framework and they have the optimality and asymptotic stability. A simulation example shows the usefulness of the approach.