Optimal filtering for Itô-Stochastic continuous-time systems with multiple delayed measurements

This paper focuses on the problem of Kalman filtering for Ito stochastic continuous-time systems with multiple delayed measurements, for which very little work exist to date. For an Ito-stochastic system, its stochastic differential and integral have a significant place and are different from other stochastic systems owing to the Wiener or the Brownian process. In this paper, an Ito stochastic continuous-time system with multiple delayed measurements is first reduced to a system with delay free measurements by applying the stochastic analysis and calculus of stochastic variables. Next, the Ito differentials for the optimal filter and its error variance are derived. Finally, through an illustrative example, the performance of the designed optimal filter is verified.