Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers
The 51st Annual Conference of the Institute of Systems, Control and Information Engineers
Session ID : 2F3-3
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Host: The Institute of Systems, Control and Information Engineers

Optimization of the Observations for the Kalman Filter based on a Generalized Water Filling Theorem
Yoshiki Takeuchi, *Koji Sakanishi, Akihiro Hirata
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Keywords: Kalman filter, Gaussian stochastic processes, optimization of observations, mutual information
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Abstract
In this paper, we are concerned with a problem of optimal selection of the gain matrix of a linear observation for the stationary Kalman filter. By introducing an information theoretic constraint based on a generalized Water Filling Theorem, we obtain a gain matrix which minimizes the stationary error variance.
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© 2007 The Institute of Systems, Control and Information Engineers
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