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摘要: 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. 仿真例子说明了其有效性.
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关键词:
- 状态估计 /
- Wiener状态滤波器 /
- 现代时间序列分析分法
Abstract: 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.
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