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

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish
Pages (from-to)2723-2731
Number of pages9
JournalJournal of the Acoustical Society of America
Issue number5
StatePublished - May 1 2016


Dive into the research topics of 'Acoustic firearm discharge detection and classification in an enclosed environment'. Together they form a unique fingerprint.

Cite this