A new multi-scale sequential data fusion scheme

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
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, data fusion problem involved non-2
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sampled observation data still hasnpsilat 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
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sampled multi-sensor dynamic system by analyzing the possible observation structure of non-2
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sampled sensor. Simulation of three sensors with sampling interval 1, 2 and 3 shows the efficiency of this scheme.