引用本文:孙书利, 崔平远.带白色和有色观测噪声系统解耦Wiener状态估值器[J].控制理论与应用,2003,20(3):371~376.[点击复制]
SUN Shu-li, CUT Ping-yuan.Decoupling Wiener state estimators for systems with white and colored observation noises[J].Control Theory and Technology,2003,20(3):371~376.[点击复制]
带白色和有色观测噪声系统解耦Wiener状态估值器
Decoupling Wiener state estimators for systems with white and colored observation noises
摘要点击 1691  全文点击 1576  投稿时间：2001-09-17  修订日期：2002-04-29
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DOI编号  10.7641/j.issn.1000-8152.2003.3.010
  2003,20(3):371-376
中文关键词  Kalman滤波器  Wiener状态估值器  ARMA新息模型  解耦  有色噪声
英文关键词  Kalman filter  Wiener state estimators  ARMA innovation model  decoupling  colored noise
基金项目  国防基础科研基金(J1600B001).
作者单位E-mail
孙书利, 崔平远 哈尔滨工业大学 深空探测基础研究中心, 黑龙江 哈尔滨 150001
黑龙江大学 自动化系, 黑龙江 哈尔滨 150080 		sunsl@hlju.edu.cn 
中文摘要
      基于经典稳态Kalman滤波理论, 对带白色和有色观测噪声系统提出了设计最优Wiener状态估值器的新方法. 通过稳态Kalman滤波器建立ARMA新息模型, 由稳态最优非递推Kalman状态估值器的递推变形引出Wiener状态估值器, 可统一处理滤波、预报和平滑问题, 它们具有状态解耦的ARMA递推形式, 且具有渐近稳定性和最优性, 仿真结果表明了算法的有效性.
英文摘要
      Based on classical steady-state Kalman filtering theory, a new approach of designing optimal Wiener state estimators is presented for the system with white and colored observation noises. The autoregressive moving average( ARMA) innovation model is yielded by steady-state Kalman filter, and the recursive versions of non-recursive steady-state optimal Kalman state estimators yield the Wiener state estimators, which can solve the filtering, prediction and smoothing problems in a unified framework. They have the state-decoupling ARMA recursive forms, and have asymptotic stability and optimality. Simulation results show their effectiveness.