Title :
Decomposition of the extended Kalman filter
Author_Institution :
University of Alberta, Edmonton, Alberta, Canada
fDate :
6/1/1971 12:00:00 AM
Abstract :
The use of the extended Kalman filter as an approximate estimator for the states and parameters of nonlinear systems is well known. A decomposition is pointed out in this letter, which is possible with the usual augumentations of the state space by parameters, and which may lead to a more efficient computing algorithm.
Keywords :
Decoupling of systems; Discrete-time systems, nonlinear; Kalman filtering; Nonlinear systems, discrete-time; Parameter estimation; Covariance matrix; Differential equations; Filtering; Filters; Matrix decomposition; Noise measurement; Stochastic processes; Stochastic resonance; Stochastic systems; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1971.1099709
