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Optimal state-vector estimation for non-Gaussian initial state-vector

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3 Author(s)
D. Lainiotis ; University of Texas, Austin, TX, USA ; S. Park ; R. Krishnaiah

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.

Published in:

IEEE Transactions on Automatic Control  (Volume:16 ,  Issue: 2 )