Multisensor Distributed Information Fusion White Noise Wiener Deconvolution Estimator

Multisensor distributed information fusion white noise wiener deconvolution estimator is presented in this paper. The algorithm is using the modern time series analysis method and white noise estimator under the linear minimum variance optimal fusion criterion. Gevers-Wouters (G-W) algorithm are also used in this paper. This paper presents information fusion algorithm including scalar weighted and covariance intersection fusion. The algorithm analyzes the relationship between the accuracy and the computation of the two fusion algorithm. The formula of optimal weighting coefficients is given. Compared with the single sensor case, the accuracy of the fused filter is greatly improved. It can be applied to signal processing in oil seismic exploration, communication and other fields. A simulation example for information fusion BernoulliGaussian white noise deconvolution filter shows its correctness and effectiveness.