OBSERVABILITY, EIGENVALUES, AND KALMAN FILTERING
OBSERVABILITY, EIGENVALUES, AND KALMAN FILTERING
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DOI：
10.1109/taes.1983.309446
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发表时间：
1983-01-01
影响因子：
4.4
通讯作者：
BROWN, RG
中科院分区：
文献类型：
--
作者：
HAM, FM;BROWN, RG
在高阶卡尔曼滤波应用中，分析人员通常对系统可观测性的本质知之甚少。例如，在某些情况下，滤波器可能很好地估计状态变量的某些线性组合，但从误差协方差矩阵来看，这一点并不明显。这里表明，误差协方差矩阵的特征值和特征向量在适当归一化时可以提供有关系统可观测性的有用信息。
In higher order Kalman filtering applications the analyst often has very little insight into the nature of the observability of the system. For example, there are situations where the filter may be estimating certain linear combinations of state variables quite well, but this is not apparent from a glance at the error covariance matrix. It is shown here that the eigenvalues and eigenvectors of the error covariance matrix, when properly normalized, can provide useful information about the observability of the system.