Optimal Kalman filtering for systems with unknown inputs

In this paper, we consider the state estimation for dynamic system with unknown inputs by difference method. We proposed an optimal algorithm in mean square error sense. The new algorithm shows good performance with less computations compared to that of traditional algorithms. Moreover, numerical examples show that the new algorithm still works well even with the wrong initial value of unknown inputs.