Non-augmented state estimation for nonlinear stochastic coupling networks

Abstract

This paper considers the state estimation problem for discrete-time nonlinear stochastic coupling networks. A non-augmented filter is designed for each node to guarantee an optimized upper bound on the state estimation error covariance matrix despite nodes coupling as well as the linearization errors. Compared with the existing augmented filter, the cross-covariance matrices between coupling nodes are not required to be computed and the gain matrix can be obtained separately for each node by solving two Riccati-like difference equations.