稳态Kalman滤波器增益新算法
New Algorithms of Stead-State Kalman Filter Gain
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摘要: 应用现代时间序列分析方法,基于ARMA新息模型,提出了稳态Kalman滤波器增 益的两种简单的新算法,并证明了它们的等价性.应用ARMA新息模型参数的递推辨识器 伴随新算法,可实现自校正Kalman滤波器.仿真例子说明了其有效性.
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关键词:
- 稳态Kalman滤波器增益 /
- 自校正Kamlan滤波器 /
- 现代时间序列分析方法
Abstract: By using the modern time series analysis method and based on the ARMA innovation model, two new algorithms of steady-state Kalman filter gain are presented, and their equivalence is proved. The self-tuning Kalman filters can be implemented by using a recursive identifier of parameters for the ARMA innovation model, in conjunction with the new algorithms. A simulation example shows usefulness of the proposed algorithms.
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