KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Hit Rate Prediction Algorithm for Laser Guided Bombs Using Image Processing

영상처리 기술을 활용한 레이저 유도폭탄 명중률 예측 알고리즘

  • 안영환 (국방대학교 컴퓨터공학과) ;
  • 이상훈 (국방대학교 컴퓨터공학과)
  • Received : 2014.11.20
  • Accepted : 2014.12.22
  • Published : 2015.03.15
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Abstract

Since the Gulf War, air power has played a key role. However, the effect of high-tech weapons, such as laser-guided bombs and electronic optical equipment, drops significantly if they do not match the weather conditions. So, aircraft that are assigned to carry laser-guided bombs must replace these munitions during bad weather conditions. But, there are no objective criteria for when weapons should be replaced. Therefore, in this paper, we propose an algorithm to predict the hit rate of laser-guided bombs using cloud image processing. In order to verify the accuracy of the algorithm, we applied the weather conditions that may affect laser-guided bombs to simulated flight equipment and executed simulated weapon release, then collected and analyzed data. Cloud images appropriate to the weather conditions were developed, and applied to the algorithm. We confirmed that the algorithm can accurately predict the hit rate of laser-guided bombs in most weather conditions.

걸프전 이후 항공력은 전쟁 승리의 핵심 역할을 수행하였다. 하지만 레이저 유도폭탄, 전자광학 장비 같은 첨단무기들은 기상 조건이 맞지 않으면 그 효과가 크게 떨어진다. 따라서 레이저 유도폭탄이 할당된 항공기는 기상 악화 시 무장교체가 이루어져야 한다. 하지만 현재까지 무장교체 시기에 대한 객관적인 기준은 없다. 따라서 본 논문에서는 구름 영상을 처리하여 레이저 유도폭탄의 명중률을 예측하는 알고리즘을 제안한다. 알고리즘의 정확도를 검증하기 위해 레이저 유도폭탄에 영향을 미칠 수 있는 기상 상황을 모의 비행장비에 적용하고 모의 무장투하를 실시하여 데이터를 수집 및 분석하였다. 모의 비행장비에 적용한 기상 조건과 유사한 구름 영상을 제작하여 알고리즘에 적용한 결과 대부분의 기상 조건에서 레이저 유도폭탄의 명중률을 정확하게 예측할 수 있음을 확인하였다.

Keywords

References

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