Robust filtering with missing data and a deterministic description of noise and uncertainty
Andrey V. Savkin, Ian R. Petersen · International Journal of Systems Science · 1997
The paper considers the problem of robust state estimation for the case in which some of the measurement data is missing. This problem is considered within the framework of a class of uncertain discrete-time systems with a deterministic description of noise and uncertainty. The main result is a recursive scheme for constructing an ellipsoidal state estimation set of all states consistent with the available measured output and the given noise and uncertainty description.