Wiener状态去卷滤波器

Wiener State Deconvolution Filters

应用现代时间序列分析方法 ,基于ARMA新息模型提出了一类带多重观测滞后和带滑动平均 (MA)有色观测噪声系统的Wiener状态去卷滤波器 .它具有渐近稳定性和ARMA递推形式 ,可统一处理滤波、平滑和预报问题 ,且可用于解决带ARMA有色观测噪声系统状态估计和信号Wiener滤波与反卷积问题 .二个仿真例子说明了其有效性 .

Using the modern time series analysis method, based on ARMA innovation model, the Wiener state deconvolution filters are presented for a class of systems with multiple measurement delays and with moving average(MA) coloured measurement noises. They have the asymptotic stability and autoregressive moving average (ARMA) recursive form. They can handle filtering, smoothing and prediction problems in a unified framework, and can be applied to solve the state estimation problem for systems with ARMA coloured measurement noise, and signal Wiener filtering and deconvolution problems. Two simulation examples show their effectiveness.