Multisensor optimal information fusion white noise deconvolution filter
多传感器最优信息融合白噪声反卷积滤波器

Using the modern time series analysis method and white noise estimation theory and based on the linear minimum variance optimal information fusion criterion weighted by scalars,a distributed fusion white noise deconvolution filter is presented for multisensor single channel systems with white and colored measurement noises.The proposed filter consists of weighting local white noise deconvolution filters,which can handle the fused filtering,smoothing,and prediction problems in a unified framework.The formula for computing the cross-covariances among local filtering errors is also given,which is applied to compute the optimal weights.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.Finally,a simulation example for information fusion Bernoulli-Gaussian white noise deconvolution filter with three-sensor shows its effectiveness.