Abstract

Synthetic Aperture Sonar (SAS) acoustic scattering data from a variety of underwater munitions was collected in the Target and Reverberation Experiment 2013 (TREX13), Bay Experiment 2014 (BayEX14) and from the Acoustic Test Facility at Naval Surface Warfare Center Panama City Division. One data product from these tests is two dimensional templates of back scattered acoustic intensity as a function of aspect angle and frequency. A common method of target classification utilizes normalized template cross-correlations as the input into classification algorithms. This is typically done in a manner agnostic to observable physics-based scattering phenomena derived from the physical size, material composition, and geometry of the targets that might help improve classification performance. This presentation discusses methods explored to process the available data to make target elastic phenomena easier to recognize so that associated information can be extracted and used as target classifier input. The methods ex...

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