Two-sensor Self-tuning Information Fusion White Noise Wiener Deconvolution Filter

By the modern time series analysis method, based on the on-line identification of the autoregressive moving aver-age (ARMA) innovation model, a self-tuning information fusion white noise Wiener deconvolution filter is presented for two-sensor deconvolution systems with unknown model parameters and unknown noise variances. It has asymptotic optimality. Asimulation example for Bemoulli-Gaussian white noise deconvolution shows its effectiveness.