Multisensor optimal information fusion white noise deconvolution filter

Abstract

Using the modern time series analysis method and white noise estimation theory, under the linear minimal variance optimal information fusion criterion, a multisensor information fusion white noise deconvolution filter is presented for systems with correlated noises. The formula of computing covariances among filtering errors of sensors is presented, which can be applied to compute the optimal fused weighting matrices. Compared with the single sensor case, the accuracy of the fused filter is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for information fusion Bernoulli-Gaussian white noise deconvolution filter shows its effectiveness.