稳态偏置卡尔曼滤波器的降阶分解

Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341) Pub Date : 1998-05-24 DOI:10.1109/CCECE.1998.682539

D. Popescu, Z. Gajic

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引用次数: 0

摘要

考虑了存在一个常数但未知的偏置向量b时线性系统状态x的估计问题。应用奇异摄动系统最优滤波的结果，得到了状态和偏置的降阶滤波器。所提出的方法完全解耦状态滤波器和偏置滤波器，它们都由系统测量驱动，从而允许并行计算。

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Reduced order decomposition for steady state biased Kalman filters

The problem of estimating the state x of a linear system in the presence of a constant, but unknown bias vector b is considered. Applying results derived for optimal filtering of singularly perturbed systems, the reduced order filters for state and bias are obtained. The presented approach completely decouples state and bias filters, both of them being driven by the systems measurements, thus allowing parallel computations.

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Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341)

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