Optimal State Estimators for Linear Systems with Unknown Inputs

We present a method for constructing linear minimum-variance unbiased state estimators for discrete-time linear stochastic systems with unknown inputs. Our design provides a characterization of estimators with delay, which eases the established necessary conditions for existence of unbiased estimators with zero-delay. A consequence of using delayed estimators is that the noise affecting the system becomes correlated with the estimation error. We handle this correlation by increasing the dimension of the estimator appropriately