Distributed descriptor Wiener state fuser

By the modem time series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimation theory, using the optimal fusion rule weighted by scalars for components, a distributed descriptor Wiener state fuser is presented for the linear discrete stochastic descriptor systems with multisensor. It realizes a decoupled fusion estimation for state components. In order to compute the optimal weights, the formulas of computing the cross-covariances among local state estimation errors are presented based on the cross-covariances among the white noises and local innovation processes. It can handle the fused filtering, smoothing, and prediction problems in a unified framework. Its accuracy is higher than that of each local estimator. A Monte Carlo simulation example shows its effectiveness.