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2007 IEEE/SP 14th Workshop on Statistical Signal Processing
This paper discusses an approach for the classification of objects in Synthetic Aperture Sonar (SAS) images and its benefit over other approaches. Our approach fully utilizes raw sonar waveforms scattered from objects. To do so, we first locate objects of interest in an image obtained by SAS processing. Then we extract the portions of the raw sonar waveforms responsible for forming those imaged objects from the whole raw sonar data. We align/straighten these extracted waveforms for localizeddoi:10.1109/ssp.2007.4301295 fatcat:xg236cmcunf7lkleud6hu3zrcy