Fusion and estimation of dynamic multiscale system based on M-band wavelet

In this paper, the fusion and estimation algorithm of a class of dynamic multiscale systems is investigated. This system is subject to the known dynamic system model, and is measured by multiple sensors with different sampling rates. The sampling rates decrease by a factor of M(M > 2). M-band wavelet is used to approximate the projection relationship between the scale spaces, and system model that satisfies Kalman filter condition is built. After performing Kalman filter, the optimal state estimation can be obtained. Simulation results are given to obtain insight into the effectiveness of our method.