Optimal information fusion estimator for discrete time systems with random delays

This paper is concerned with the multi-sensor optimal information fusion issues for discrete-time systems with random delayed which is time-stamped. The random delayed system is reconstructed as an equivalent delay-free one by means of the measurement reorganization technique when the random delay is time-stamped. Based on the altered system model, firstly an optimal linear filter is presented for each sensor by the projection formula. And then the state fusion estimation is developed by applying the scalar-weighted fusion method. Note that the fusion estimation has high accuracy and has the same dimension as the original systems, which reduces the computational burden greatly. Finally, a numerical example is presented to illustrate the efficiency of proposed estimators.