Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Implementation of JDAM virtual training function using machine learning

  • Received : 2020.07.20
  • Accepted : 2020.11.09
  • Published : 2020.11.30
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Abstract

The TA-50 aircraft is conducting simulated training on various situations, including air-to-air and air-to-ground fire training, in preparation for air warfare. It is also used for pilot training before actual deployment. However, the TA-50 does not have the ability to operate smart weapon forces, limiting training. Therefore, the purpose of this study is to implement the TA-50 aircraft to enable virtual training of one of the smart weapons, the Point Direct Attack Munition (JDAM). First, JDAM functions implemented in FA-50 aircraft, a model similar to TA-50 aircraft, were analyzed. In addition, since functions implemented in FA-50 aircraft cannot be directly utilized by source code, algorithms were extracted using machine learning techniques(TensorFlow). The implementation of this function is expected to enable realistic training without actually having to be armed. Finally, based on the results of this study, we would like to propose ways to supplement the limitations of the research so that it can be implemented in the same way as it is.

TA-50 항공기는 공중전에 대비하여 공대공, 공대지 사격 훈련 등 다양한 상황에 대한 모의 훈련을 수행하고 있다. 또한 조종사의 실전 배치 전 훈련용으로도 사용되고 있다. 그러나 TA-50은 스마트 무장 운용 능력을 보유하고 있지 않아 훈련에 제한이 되고 있다. 이에 본 연구에서는 TA-50 항공기에 스마트 무장 중 하나인 합동정밀직격탄(JDAM)의 가상훈련이 가능하도록 구현하고자 하였다. 먼저, TA-50 항공기와 유사한 기종인 FA-50 항공기에 구현된 JDAM 기능을 분석하였다. 또한 FA-50 항공기에 구현된 기능은 소스코드의 직접 활용이 불가능하므로 머신러닝 기법(TensorFlow)을 활용하여 알고리즘을 추출하였다. 본 기능을 구현함으로써 실 무장을 장착하지 않아도 실제와 유사한 훈련이 가능할 것으로 기대된다. 마지막으로 본 연구 결과를 바탕으로 연구의 한계점을 보완하여 실제와 동일하게 구현할 수 있는 방안을 제안하고자 한다.

Keywords

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