Ensemble Kalman filtering for nonlinear systems with multiple delayed measurements

The ensemble Kalman filter (EnKF) is developed to nonlinear discrete-time systems with multiple delayed measurements. An explicit and simpler solution to the ensemble Kalman filtering problem is presented for such systems, which is slightly modified that the members of measurement ensemble are obtained from uncorrelated sensors in the system but not a Monte Carlo method. The approach applied is the reorganized innovation analysis. A numerical example with a bank-to-turn (BTT) missile autopilot model is given to demonstrate the proposed approach.