A NEW MULTI-SCALE SEQUENTIAL DATA FUSION SCHEME

摘要

Researches on multi-scale data fusion have become a hot topic in data fusion field. However, limited by the constraint that signal to implement wavelet transform must have the length of 2", data fusion problem involved non-2' sampled observation data still hasn't been efficiently solved. In this paper, we aim to develop a new sequential fusion scheme by designing the stacked observation model for hybrid wavelet-Kalman filter based sequential data fusion method for the fusion of non-2" sampled multi-sensor dynamic system by analyzing the possible observation structure of non- 2" sampled sensor. Simulation of three sensors with sampling interval 1, 2 and 3 shows the efficiency of this scheme.