Gaussian Acoustic Classifier for the Launch of Three Weapon Systems

Report No. ARL-TN-0576
Authors: Christine Yang and Geoffrey Goldman
Date/Pages: September 2013; 24 pages
Abstract: The U.S. Army is interested in locating and classifying hostile weapons fire to improve the Soldiers real-time situational awareness. Acoustic localization systems such as the Unattended Transient Acoustic MASINT System (UTAMS) have been demonstrated in theater. However, developing a classifier algorithm is a difficult problem due to atmospheric and propagation effects as well as acoustic interference and noise. Techniques were developed to accurately classify acoustic weapons system fire. Robust features were calculated in the time domain and used to train a Gaussian classifier. The algorithm was tested and trained using data collected in 2005, 2006, and 2011. The performance of the algorithm was similar to the results obtained by other researchers, but with significantly less computational complexity.
Distribution: Approved for public release
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Last Update / Reviewed: September 1, 2013