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Proceedings Paper

Feature extraction from time domain acoustic signatures of weapons systems fire
Author(s): Christine Yang; Geoffrey H. Goldman
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Paper Abstract

The U.S. Army is interested in developing algorithms to classify weapons systems fire based on their acoustic signatures. To support this effort, an algorithm was developed to extract features from acoustic signatures of weapons systems fire and applied to over 1300 signatures. The algorithm filtered the data using standard techniques then estimated the amplitude and time of the first five peaks and troughs and the location of the zero crossing in the waveform. The results were stored in Excel spreadsheets. The results are being used to develop and test acoustic classifier algorithms.

Paper Details

Date Published: 4 June 2014
PDF: 9 pages
Proc. SPIE 9082, Active and Passive Signatures V, 90820E (4 June 2014); doi: 10.1117/12.2070455
Show Author Affiliations
Christine Yang, U.S. Army Research Lab. (United States)
Geoffrey H. Goldman, U.S. Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 9082:
Active and Passive Signatures V
G. Charmaine Gilbreath; Chadwick Todd Hawley, Editor(s)

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