KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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A Study on the Detection of Small Arm Rifle Sound Using the Signal Modelling Method

신호 모델링 기법을 이용한 소총화기 신호 검출에 대한 연구

  • 신민철 (단국대학교 소프트웨어학과) ;
  • 박규식 (단국대학교 소프트웨어학과)
  • Received : 2015.04.08
  • Accepted : 2015.04.29
  • Published : 2015.07.15
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Abstract

This paper proposes a signal modelling method that can effectively detect the shock wave(SW) sound and muzzle blast(MB) sound from the gunshot of a small arm rifle. In order to localize a counter sniper in battlefield, an accurate detection of both shock wave sound and muzzle blast sound are the necessary keys in estimating the direction and the distance of the counter sniper. To verify the performance of the proposed algorithm, a real gunshot sound in a domestic military shooting range was recorded and analyzed. From the experimental results, the proposed signal modelling method was found to be superior to the comparative system more than 20% in a shock wave detection and 5% in a muzzle blast detection, respectively.

본 논문에서는 신호 모델링 기법을 이용하여 소총화기에서 발생하는 탄환충격파(SW, Shock Wave) 음향신호와 총성(MB, Muzzle Blast) 음향신호를 효과적으로 검출할 수 있는 알고리즘을 제안하였다. 전장에서 저격수의 위치를 탐지하기 위해서는 저격수의 소총화기에서 발생하는 탄환충격파와 총성 신호를 정확하게 검출하여 적 저격수의 방향각과 거리를 추정하는 것이 중요하다. 제안 알고리즘의 성능을 검증하기 위하여 국내 군 사격장에서 실제 소총화기 발사 실험을 진행하였고, 실험결과 제안 알고리즘은 탄환충격파 신호 검출에 있어 기존 알고리즘에 비해 최대 20% 가까운 성능향상을, 총성 신호 검출에 있어서는 약 5% 정도의 성능향상을 가져옴을 확인할 수 있었다.

Keywords

Acknowledgement

Supported by : 방위사업청

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