Hidden state estimation in the state space model with first-order autoregressive process noise

Document Type: Regular Paper

Authors

1 Department of Applied Mathematics, Faculty of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844, Iran

2 Department of Applied Mathematics, Faculty of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844, Iran

Abstract

In this article, the discrete time state space model with first-order autoregressive dependent process noise is
considered and the recursive method for filtering, prediction and smoothing of the hidden state from the noisy
observation is designed. The explicit solution is obtained for the hidden state estimation problem. Finally, in a
simulation study, the performance of the designed method for discrete time state space model with dependent
process noise is verified.

Keywords