一类稳态Kalman滤波器及其渐近稳定性
A STEADY-STATE KALMAN FILTER AND ITS ASYMPTOTIC STABILITY
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摘要: 应用现代时间序列分析方法,基于ARMA新息模型和白噪声估值器,对完全可观的离散线性随机系统,提出了一类稳态Kalman滤波器,其中给出了稳态Kalman滤波器增益的两种新算法,并给出了保证滤波器渐近稳定性的初值选择公式.仿真例子说明了其有效性.Abstract: Using the modern time series analysis method,based on the ARMA innovation model and white noise estimators, a steady-state Kalman filter is presented for completely observable discrete linear stochastic systems,where two new algorithms of steady-state Kalman filter gain are given, and a formula of setting the initial value of filter is given to ensure asymptotic stability of filter. A simulation example shows its usefulness.