Multisensor Information Fusion Wiener Deconvolution Predictor

By the modern time series analysis methods, based on ARMA innovation model and augmented state space model, a multisensor optimal information fusion Wiener deconvolution predictor weighted by scalars is proposed. The formulas of computing the local predictor error variances and cross-covariances are given, which are applied to compute optimal weighting coefficients. Compared to the single sensor case, the accuracy of the fused predictor is improved. A simulation example shows its effectiveness.