Abstract
This paper proposes a wavelet-based methodology for fusing data from multiple sensors each having their own unique sampling rate. The aim of this work is to integrate information from such complementary sensors and to be able to work with information having different time resolutions. Present fusion methods have difficulty in dealing with such multiresolution data. In this work, wavelet transforms, with their multiresolution properties, are applied to decompose signals to a common time base at which the fusion of information takes place. Simulations are used to show the effectiveness of the proposed methodology.