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带有色观测噪声系统统一的Wiener状态估值器
引用本文:石莹 孙书利 等. 带有色观测噪声系统统一的Wiener状态估值器[J]. 科学技术与工程, 2003, 3(2): 109-111
作者姓名:石莹 孙书利 等
作者单位:黑龙江大学自动化系,哈尔滨,150080
基金项目:国家自然科学基金(69774019),黑龙江省自然科学基金(F01-15)
摘    要:通过对观测方程的线性变化,将带有色观测噪声系统化为带白色观测噪声的系统。基于自回归滑动平均(ARMA)新息模型,由稳态最优Kalman估值器导出了渐近稳定的Wiener状态估值器,可统一处理滤波、平滑和预报问题。一个仿真例子说明它们的有效性。

关 键 词:状态估计 有色观测噪声 Wiener状态估值器 Kalman滤波方法
文章编号:1671-1815(2003)02-0109-03
修稿时间:2002-12-03

Unified Wiener State Estimators for Systems with Coloured Observation Noise
SHI Ying,SUN Shuli,XU Yan,DENG Zili Department of Automation,Heilongjiang University,Harbin. Unified Wiener State Estimators for Systems with Coloured Observation Noise[J]. Science Technology and Engineering, 2003, 3(2): 109-111
Authors:SHI Ying  SUN Shuli  XU Yan  DENG Zili Department of Automation  Heilongjiang University  Harbin
Affiliation:SHI Ying,SUN Shuli,XU Yan,DENG Zili Department of Automation,Heilongjiang University,Harbin 150080
Abstract:By means of a linear transformation of the observation equation, the system with coloured observation noise istransformed into the system with white observation noise. Based on the autoregressive moving average (ARMA) innovation mod-el, the asymptotically stable Wiener state estimators are derived via the steady-state optimal Kalman estimators. They can han-dle the filtering, smoothing and prediction problems in a unified framework. A simulation example shows their effectiveness.
Keywords:state estimation  coloured observation noise  Wiener state estimators  Kalman filtering method
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