Krein space approach to robust H_∞ filtering for GNSS/SINS integrated navigation system with missing measurements

In this paper, Krein space approach to robust H_∞ filtering for uncertain systems with missing measurement is developed. The unavailablesystem measurements may occur at any time with a known conditional probability distribution. The parameter uncertainties are allowed to be norm-bounded. The purpose of this problem is to minimize a second-order form through Krein-space robust estimation such that, for all parameter uncertainties and all random missing observations, the estimated states are bounded in an ellipsoidal set. M-P inverse has to be introduced to design Krein space formal system. Then Riccati-styled recursion is obtained in the Krein space state-space structure. It is shown that the objective quadratic form is minimized if a necessary and sufficient condition is satisfied. Finally, the numerical examples illustrate the performance of the proposed filter.