An alternate algorithm for discrete-time filtering

The discrete-time Kalman filter is an optimal estimator for the states of a linear, stochastic system. It assumes that measurements are linear combinations of the states, and all disturbances are Gaussian. The influence diagram, a decision analysis tool that provides an algorithm for discrete-time f...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 1993-10, Vol.29 (4), p.1123-1136
Main Authors: Zeitz, F.H., Maybeck, P.S.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Applied sciences
Computer errors
Covariance matrix
Detection, estimation, filtering, equalization, prediction
Eigenvalues and eigenfunctions
Exact sciences and technology
Filtering algorithms
Information, signal and communications theory
Nonlinear filters
Random variables
Roundoff errors
Signal and communications theory
Signal, noise
State estimation
Stochastic systems
Telecommunications and information theory
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Summary:The discrete-time Kalman filter is an optimal estimator for the states of a linear, stochastic system. It assumes that measurements are linear combinations of the states, and all disturbances are Gaussian. The influence diagram, a decision analysis tool that provides an algorithm for discrete-time filtering equivalent to the Kalman filter when the influence diagram represents Gaussian random variables, is discussed. The influence diagram algorithm is a factored form of the Kalman filter, similar to other factored forms such as the U-D filter. Compared with the Kalman filter, it offers improved numerical properties. Compared with other factored forms, it offers a reduced computational load.< >
ISSN:0018-9251
1557-9603
DOI:10.1109/7.259516