Abstract
Using the projection theory and modern time series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimators, the reduced-order Wiener state estimators for descriptor system with MA colored observation noise and multi-observation lags are presented. They can handle the prediction, filtering and smoothing in a unified framework. They avoid the solutions of the Riccati equations and Diophantine equations. The estimators have the ARMA recursive form and have asymptotic stability. A simulation example shows their effectiveness.
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