2016
DOI: 10.1121/1.4948994
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Acoustic firearm discharge detection and classification in an enclosed environment

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.

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Cited by 6 publications
(3 citation statements)
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“…This will maximize drone detection while filtering out other acoustic sources. More details on these types of acoustic sources can be found in [49][50][51][52][53]. Figure 15a,b shows the typical acoustic signatures of pistol gunfire and a small fourrotor drone, respectively, measured with a broadband microphone (Piezotronics Model 378A21).…”
Section: Operation In Airmentioning
confidence: 99%
See 1 more Smart Citation
“…This will maximize drone detection while filtering out other acoustic sources. More details on these types of acoustic sources can be found in [49][50][51][52][53]. Figure 15a,b shows the typical acoustic signatures of pistol gunfire and a small fourrotor drone, respectively, measured with a broadband microphone (Piezotronics Model 378A21).…”
Section: Operation In Airmentioning
confidence: 99%
“…This will maximize drone detection while filtering out other acoustic sources. More details on these types of acoustic sources can be found in [49][50][51][52][53].…”
Section: Operation In Airmentioning
confidence: 99%
“…However, while shotguns and artillery report is considered to be just a noise, it can be in fact very informative. Acoustic signal of a firearm discharge can be detected and classified [3]. For example, Defense Technical Information Center published a study of the spectral content of small arms fire at varying distances [4].…”
Section: Introductionmentioning
confidence: 99%