Kalman Filter Modeling

R. Grover Brown

Abstract:	The main emphasis of this tutorial paper is on the formulation of appropriate state-space models for Kalman filtering applications. The so-called "model" is completely specified by four matrix parameters and the initial conditions of the recursive equations. Once these are determined, the die is cast, and the way in which the measurements are weighted is determined foreverafter. Thus, finding a model that fits the physical situation at hand is all important. Also, it is often the most difficult aspect of designing a Kalman filter. Formulation of discrete state models from the spectral density and ARMA random process descriptions is discussed. Finally, it is pointed out that many common processes encountered in applied work (such as band-limited white noise) simply do not lend themselves very well to Kalman filter modeling.
Published in:	Proceedings of the 16th Annual Precise Time and Time Interval Systems and Applications Meeting November 27 - 29, 1984 NASA Goddard Space Flight Center Greenbelt, Maryland
Pages:	261 - 272
Cite this article:	Brown, R. Grover, "Kalman Filter Modeling," Proceedings of the 16th Annual Precise Time and Time Interval Systems and Applications Meeting, Greenbelt, Maryland, November 1984, pp. 261-272.
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