In order to compute the optimal weighting matrices, the formula of computing the cross-covariance matrices among local filtering errors, is presented.
为了计算最优加权阵，提出了计算局部滤波误差互协方差阵的公式。
In order to compute the optimal weighting matrices, the formula of computing the cross-covariance matrix between local estimation errors is presented.
为了计算最优加权阵，提出了局部估计误差互协方差阵的计算公式。
The formulas of computing the variance and cross-covariance matrices among local state estimation errors are presented, which are applied to compute the optimal weights.
为了计算最优加权，提出了状态估计误差方差阵和互协方差阵的计算公式。
In order to compute the optimal weights, the formulas of computing the local estimation error covariance and cross-covariance matrices are presented.
为了计算最优加权，提出了局部估计误差方差阵和互协方差阵的计算公式。
In order to compute the optimal weights, the formula of computing the cross-covariance among local filtering errors is presented.
为了计算最优加权，提出了局部估计误差互协方差的计算公式。
Then we derive the computation formula for the cross-covariance matrix between any two local estimators.
然后，推导了任两个局部估计误差之间的互协方差阵的计算公式。
The cross-covariance matrix of filtering errors between any two-sensor subsystems is derived for state time-delay systems.
任意两个传感器子系统之间的滤波误差互协方差矩阵推导出状态的时间延迟系统。
The cross-covariance matrix of filtering errors between any two-sensor subsystems is derived for state time-delay systems.
任意两个传感器子系统之间的滤波误差互协方差矩阵推导出状态的时间延迟系统。
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