Multiresolutional filtering of a class of dynamic multiscale system subject to colored measurement noise

Multiresolutional filtering of a class of dynamic multiscale system subject to colored measurement noise is proposed. A new measurement is introduced at each scale, the state space projection equation is used to link the scales, and then a new system model is built. The new model is in a form suitable for the application of the Kalman filter equations. Haar-wavelet-based model and estimation algorithm are given. Monte Carlo simulation results demonstrate that the proposed algorithm is effective and powerful in this kind of multiscale estimation problem.