Sampled-data filtering with error covariance assignment
Sampled-data filtering with error covariance assignment
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DOI：
10.1109/78.905899
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发表时间：
2001-03
期刊：
影响因子：
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通讯作者：
Zidong Wang;Biao Huang;Peijun Huo
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文献类型：
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作者：
Zidong Wang;Biao Huang;Peijun Huo
我们考虑采样数据滤波问题，提出了一个新的性能标准的估计误差协方差。提出了一种新的采样数据滤波方法。首先给出了采样数据系统估计协方差e的定义，然后将采样数据滤波问题归结为一个虚拟离散系统的卡尔曼滤波器设计问题，最后给出了一种有效的设计离散卡尔曼滤波器的方法，使得得到的采样数据估计协方差达到一个预定值。我们推导出所需的过滤器的存在条件和明确的表达，并提供了一个说明性的数值例子来证明本设计方法的直接性和灵活性。
We consider the sampled-data filtering problem by proposing a new performance criterion in terms of the estimation error covariance. An innovation approach to sampled-data filtering is presented. First, the definition of the estimation covariance e for a sampled-data system is given, then the sampled-data filtering problem is reduced to the Kalman filter design problem for a fictitious discrete-time system, and finally, an effective method is developed to design discrete-time Kalman filters in such a way that the resulting sampled-data estimation covariance achieves a prescribed value. We derive both the existence conditions and the explicit expression of the desired filters and provide an illustrative numerical example to demonstrate the directness and flexibility of the present design method.