Abstract:

The optimal input white noise estimator for linear discretetime systems with delayed measurements is studied by using Kalman filtering. The delayed measurements are reorganized as that without delay, then the reorganized innovation is given. Based on the projection theorem in Hilbert Spaces, the proposed approach is given in terms of two Riccati difference equations (RDEs) with the same order as that of the original system. The approach can improve the computational efficiency without resorting to system state augmentation. A numerical example is given and the simulation results show the effectiveness of the proposed method.

Key words: white noise estimators; reorganized innovation; Ric cati equation; timedelay systems; deconvolution