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영어

Multisensor distributed fusion Wiener deconvolution estimator is presented in this paper. It does not need to solve the Diophantine equation, and the steady-state Kalman filter gain of the augmented system. It can handle processing of nonstationary signal. White noise estimator and Astrom predictor are used in the algorithm. Gevers-Wouters (G-W) algorithm is also used in this paper. In order to improve the estimation precision, multisensor information fusion Wiener deconvolution estimator for multichannel system is proposed in this paper by using the modern time series analysis method. The information fusion algorithms included matrix weighted, diagonal matrices weighted, scalar weighted and covariance intersection fusion in this paper. Under the linear minimum variance optimal information fusion criterion, the calculation formula of optimal weighting coefficients have be given. The algorithm analyzes the relationship between the accuracy and the computation complexities of four fusion algorithms. Compared with the single sensor case, the accuracy of the fused filter is greatly improved. It can be applied in signal processing, communication, control field and other fields. A simulation example for multichannel ARMA signal shows its correctness and effectiveness.