System for an Acoustic Detection, Localization and Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00349856" target="_blank" >RIV/68407700:21230/21:00349856 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.21014/acta_imeko.v10i2.1041" target="_blank" >https://doi.org/10.21014/acta_imeko.v10i2.1041</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21014/acta_imeko.v10i2.1041" target="_blank" >10.21014/acta_imeko.v10i2.1041</a>

Jazyk výsledku

angličtina

Název v původním jazyce

System for an Acoustic Detection, Localization and Classification

Popis výsledku v původním jazyce

At present, acoustic detection techniques of gunshots (gunshot detection and its classification) are increasingly being used not only for military applications but also for civilian purposes. Detection, localization, and classification of a dangerous event such as gunshots employing acoustic detection is a perspective alternative to visual detection, which is commonly used. In certain situations, to detect and localize a source of a gunshot, an automatic acoustic detection system, which can classify the caliber, may be preferable. This paper presents a system for acoustic detection, which can detect, localize and classify acoustic events such as gunshots. The system has been tested in open and closed shooting ranges and tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As “false alarms,” sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. Localization and classification algorithms are also introduced. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localization, and classification.

Název v anglickém jazyce

System for an Acoustic Detection, Localization and Classification

Popis výsledku anglicky

At present, acoustic detection techniques of gunshots (gunshot detection and its classification) are increasingly being used not only for military applications but also for civilian purposes. Detection, localization, and classification of a dangerous event such as gunshots employing acoustic detection is a perspective alternative to visual detection, which is commonly used. In certain situations, to detect and localize a source of a gunshot, an automatic acoustic detection system, which can classify the caliber, may be preferable. This paper presents a system for acoustic detection, which can detect, localize and classify acoustic events such as gunshots. The system has been tested in open and closed shooting ranges and tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As “false alarms,” sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. Localization and classification algorithms are also introduced. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localization, and classification.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ACTA IMEKO

ISSN

2221-870X

e-ISSN

2221-870X

Svazek periodika

10

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

BE - Belgické království

Počet stran výsledku

8

Strana od-do

62-69

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85109493994