Multisensor information fusion white noise estimator

Based on the Kalman filtering method and white noise estimation theory, under the linear minimum variance optimal information fusion criterion weighted by matrices, the multisensor information fusion white noise deconvolution estimator is presented for systems with colored measurement noise. The formula of the cross-covariance matrices among the noise estimation errors is presented which is applied to compute the optimal weighting matrices. Compared to the single sensor case, the accuracy of fused estimation is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for 4-sensor information fusion Bernoulli-Gaussian white noise deconvolution filter shows its effectiveness.