Multichannel ARMA signal information fusion wiener estimator based on Kalman filtering
Zhuo Chen, Sun Shuli · 2008
Using Kalman filtering theory, based on the autoregressive moving average (ARMA) innovation model, the white noise estimator and the measurement predictor, a distributed information fusion Wiener estimator is presented for multichannel ARMA signal with multiple sensors by the matrix weighting fusion algorithm in the linear minimum variance sense. It has the asymptotical stability. It can handle the filtering, smoothing and prediction problems in a unified framework. A simulation example verifies its effectiveness.