Linear estimation for system with unknown measurement input and missing measurement

This paper is devoted to solving the state estimation problem for systems with unknown measurement input and missing measurement. The missing measurement phenomenon is described by a series of mutually independent random variables obeying a certain Bernoulli distribution. Firstly, our aim is to design an linear filter by applying the minimum variance unbiased estimation technique. Then, we also derive a suboptimal estimator by utilizing the time stamp technology in sensor networks. Finally, an example is supplied to show the effectiveness of the proposed filters.