Implicit Kalman filtering.

M Skliar; W F Ramirez

doi:10.1080/002071797224649

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Implicit Kalman filtering.

M Skliar·W F Ramirez

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Abstract

For an implicitly defined discrete system, a new algorithm for Kalman filtering is developed and an efficient numerical implementation scheme is proposed. Unlike the traditional explicit approach, the implicit filter can be readily applied to ill-conditioned systems and allows for generalization to descriptor systems. The implementation of the implicit filter depends on the solution of the congruence matrix equation (A1)(Px)(AT1) = Py. We develop a general iterative method for the solution of this equation, and prove necessary and sufficient conditions for convergence. It is shown that when the system matrices of an implicit system are sparse, the implicit Kalman filter requires significantly less computer time and storage to implement as compared to the traditional explicit Kalman filter. Simulation results are presented to illustrate and substantiate the theoretical developments.

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Algorithms Computer Simulation Electronic Data Processing Mathematics Models, Theoretical Stochastic Processes NASA Discipline Environmental Health Non-NASA Center Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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M Skliar, W F Ramirez. 1997. Implicit Kalman filtering.. https://doi.org/10.1080/002071797224649

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