Self-tuning information fusion white noise estimator with input estimation

For the multisensor linear discrete time-invariant systems with unknown constant input and unknown noise statistics, the on-line estimators of unknown input and unknown noise statistics are obtained based on CARMA innovation model. For the multisensor stochastic control systems with known input and noise statistics, the optimal information fusion steady-state white noise estimator is presented based on Fadeeva formula. Furthermore, a self-tuning information fusion white noise estimator with input estimation is presented. Based on the dynamic error system analysis method, its asymptotic optimality is proved, i.e. it converges to the optimal fusion steady-state white noise estimator in a realization. A simulation example for a 3-sensor system with Bernoulli-Gaussian input white noise shows its effectiveness.