Multisensor Distributed Fusion White Noise Deconvolution Filter

Based on the Kalman filtering method and white noise estimation theory, under the linear minimum variance optimal information fusion criterion weighted by matrices，a multisensor distributed fusion optimal white noise deconvolution filter is presented for systems with ARMA colored measurement noise，where the formulas of computing cross-covariances among local estimation errors by Lyapunov equations are derived，which is applied to compute optimal weights．Compared to the single sensor case， the accuracy of fused estimators is improved． It can be applied to signal processing in oil seismic exploration． A simulation example for three-sensor distributed fusion Bernoulli-Gaussian white noise deconvolution smoother shows its effectiveness．