INTERVAL KALMAN FILTERING

The classical Kalman filtering technique is extended to interval linea r system with the same statistical assumptions on noise, for which the classical technique is no longer applicable. Necessary interval analy sis, particularly the notion of interval expectation, is reviewed and introduced. The interval Kalman filter (IKF) is then derived, which ha s the same structure as the classical algorithm, using no additional a nalysis or computation from such as H-infinity-mathematics. A suboptim al IKF is suggested next, for the purpose of real-time implementation. Finally, computer simulations are shown to compare the new interval K alman filtering algorithm with the classical Kalman filtering scheme a nd some other existing robust Kalman filtering methods.