Acoustic firearm discharge detection and classification in an enclosed environment

Lorenzo Luzi; Eric Gonzalez; Paul Bruillard; Matthew Prowant; James Skorpik; Michael Hughes; Scott Child; Duane Kist; John E McCarthy

doi:10.1121/1.4948994

Acoustic firearm discharge detection and classification in an enclosed environment

J Acoust Soc Am. 2016 May;139(5):2723. doi: 10.1121/1.4948994.

Authors

Lorenzo Luzi¹, Eric Gonzalez¹, Paul Bruillard¹, Matthew Prowant¹, James Skorpik¹, Michael Hughes¹, Scott Child², Duane Kist², John E McCarthy³

Affiliations

¹ Pacific Northwest National Laboratory, Richland, Washington 99354, USA.
² Kennewick Police Department SWAT Team, 211 West 6th Avenue, Kennewick, Washington 99336-0108, USA.
³ Department of Mathematics, Washington University in Saint Louis, Campus Box 1146, St. Louis, Missouri 63130, USA.

PMID: 27250165
DOI: 10.1121/1.4948994

Abstract

Two different signal processing algorithms are described for detection and classification of acoustic signals generated by firearm discharges in small enclosed spaces. The first is based on the logarithm of the signal energy. The second is a joint entropy. The current study indicates that a system using both signal energy and joint entropy would be able to both detect weapon discharges and classify weapon type, in small spaces, with high statistical certainty.