Covariance factorization algorithms for fixed-interval smoothing of linear discrete dynamic systems

McReynolds S.R.

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Covariance factorization algorithms for fixed-interval smoothing of linear discrete dynamic systems

机译：协方差分解算法，用于线性离散动态系统的固定间隔平滑

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Efficient factorized covariance smoothers designed to work with factorized covariance filters are derived for linear discrete dynamic systems. The approach to factorized covariance smoothers (either U-D or square root) uses outputs from factorized covariance filters and is closely derived from the G.J. Bierman's earlier algorithm (1974), the Dyer-McReynolds covariance smoother. These algorithms are more efficient than the Bierman's newer smoother (1983) based upon rank 1 process noise updates. The efficiency of the new algorithms increases significantly as the order of process noise increases. For full process noise, they can be implemented in a way that avoids the inverse of the transition matrix.

机译：针对线性离散动态系统，推导了设计用于因子分解协方差滤波器的高效因子分解协方差平滑器。分解协方差平滑器（U-D或平方根）的方法使用分解协方差滤波器的输出，并且是从G.J. Bierman较早的算法（1974年），Dyer-McReynolds协方差平滑器。这些算法比基于1级过程噪声更新的Bierman较新的平滑器（1983）更为有效。新算法的效率随着过程噪声阶数的增加而显着提高。为了获得完整的过程噪声，可以采用避免转换矩阵逆的方式实现它们。

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《IEEE Transactions on Automatic Control》 |1990年第10期|P.1181-1183|共3页
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McReynolds S.R.;
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Covariance factorization algorithms for fixed-interval smoothing of linear discrete dynamic systems

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