统一的和通用的Wiener状态滤波器

UNIFIED AND UNIVERSAL WIENER STATE FILTERS

用现代时间序列分析方法 ,基于 ARMA新息模型提出了带拟白噪声、拟相关噪声和带观测滞后系统的统一的通用的渐近稳定的 Wiener状态滤波器 ,可统一处理状态滤波、平滑和预报问题 .同 Kalman滤波方法和多项式方法相比 ,避免了求解 Riccati方程和 Diophantine方程。

Using the modern time series analysis method and based on the ARMA innovation model, unified and universal Wiener state filters are presented for systems with quasi-white noise and quasi-correlated noises and with measurement delay, which can handle the state filtering, smoothing and prediction problems in a unified framework. Compared to the Kalman filtering method and polynomial method,the solution to Riccati equations and Diophantine equations is avoided. A simulation example shows their effectiveness.