DocumentCode :
805783
Title :
Optimal state-vector estimation for non-Gaussian initial state-vector
Author :
Park, Soojin
Volume :
16
Issue :
2
fYear :
1971
fDate :
4/1/1971 12:00:00 AM
Firstpage :
197
Lastpage :
198
Abstract :
The optimal estimate, in the mean-square-error sense, of state-vector of a linear system excited by zero-mean white Gaussian noise with non-Gaussian initial state-vector is obtained. Both the optimal estimate and the corresponding error covariance matrix are given. It is shown that the optimal estimator consists of two parts: a linear estimator that is obtained from a Kalman filter and a nonlinear estimator. In addition, the a posteriori probability p(x_{k}/\\lambda _{k}) is also given.
Keywords :
Linear systems, stochastic discrete-time; State estimation; Covariance matrix; Difference equations; Gaussian noise; Kalman filters; Linear systems; Maximum likelihood detection; Random processes; State estimation; Vectors;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1971.1099695
Filename :
1099695
Link To Document :
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