分离随机偏差两段解耦Wiener滤波器

Separate stochastic bias two-stage decoupled wiener filters

应用现代时间序列分析方法 ,基于ARMA新息模型和Wiener状态滤波器 ,对带随机偏差系统首次提出了分离随机偏差两段解耦Wiener滤波器 ,形成了一种新的偏差处理技术 .同传统的两段Kalman滤波器相比 ,具有如下优点 :1)可统一处理滤波、平滑和预报问题 ;2 )避免了Riccati方程的计算 ;3)具有最优性和渐近稳定性 ;4)实现了完全解耦 ;5 )便于实时应用 .两个仿真例子说明了其有效性 .

Using the modern time series analysis method,based on the ARMA innovation model and Wiener state filters,the separate stochastic bias two-stage decoupled Wiener filters are presented for the first time for systems with stochastic bias, which formed a new technique for treatment of bias.Compared to the classical two-stage Kalman filters,they have the following advantages: 1) they can handle the filtering,smoothing,and prediction problems in a unified framework; 2) the computation of the Riccati equations is avoided; 3) they have the optimality and asymptotic stability; 4) the complete decouple is implemented; 5) they are suitable for real time applications.Two simulation examples show their effectiveness.