Noise Moment and Parameter Estimation of State-Space Model

Abstract

The paper deals with the estimation of the moments and parameters of the state and measurement noises of a system described by a linear time-varying state-space model. In particular, a novel correlation measurement difference method is designed. The method is based on a statistical analysis of an augmented measurement prediction error leading to a system of linear matrix equations enabling higher-order noise moments estimation. The estimated moments, shown to converge to the true values, are then used for noise parameters computation. The theoretical results are discussed and illustrated in a numerical example.