Multisensor information fusion white noise deconvolution filter with colored noise

Based on the Kalman filtering method and white noise estimation theory, under linear minimum variance information fusion criterion weighted by scalars, a multisensor optimal information fusion white noise deconvolution filter is presented for multisensor systems with system deviation,ARMA colored measurement noise and white noise. The formula of computing cross-covariances among filtering errors of sensors is presented, which can be applied to compute the optimal fused weighting coefficients. Compared to the single sensor case, the accuracy of fused filtering is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for 3-sensor information fusion Bernoulli-Gaussian white noise deconvolution filter shows its effectiveness.