Robust transcale state estimation for multiresolution discrete-time systems based on wavelet transform

In this study, an effective robust transcale estimation algorithm is proposed for discrete-time systems, which are observed by a single sensor at the finest resolution or by two sensors at the finest and coarsest resolutions. The discrete-time state-space models of approximation and detail coefficients at each resolution are established by using Haar wavelet decomposition, respectively. The algorithm is developed based on the standard H_∞ filtering scheme, and hence preserves the merits of the H_∞ filter for random signal estimation in the sense that it minimises the effect of the worst possible disturbances on the estimation errors. The proposed algorithm is demonstrated through Monte Carlo simulations involving tracking of a target in CV model.