Self-tuning Measurement Fusion Decoupled Wiener State Predictor

For the multisensor systems with unknown noise variances, and with diffrernt measurement matrices, using the modern time series analysis method, based on the on-line identification of the moving average (MA) innovation models of the subsystems and weighted measurement fusion system, a class of the self-tuning weighted measurement fusion decoupled Wiener state predictors is presented. By the dynamic error system analysis method, it is proved that it converges to the optimal weighted measurement fusion decoupled Wiener state predictor with known noise variances in a realization, so that it has asymptotic global optimality. A simulation example for a target tracking system shows its effectiveness.