Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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Research for Drone Target Classification Method Using Deep Learning Techniques

딥 러닝 기법을 이용한 무인기 표적 분류 방법 연구

  • 최순현 (한국과학기술원 전기및전자공학부) ;
  • 조인철 (LIG넥스원(주) 레이다 연구소) ;
  • 현준석 (LIG넥스원(주) 레이다 연구소) ;
  • 최원준 (LIG넥스원(주) 레이다 연구소) ;
  • 손성환 (LIG넥스원(주) 레이다 연구소) ;
  • 최정우 (한국과학기술원 전기및전자공학부)
  • Received : 2023.12.05
  • Accepted : 2024.02.15
  • Published : 2024.04.05
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Abstract

Classification of drones and birds is challenging due to diverse flight patterns and limited data availability. Previous research has focused on identifying the flight patterns of unmanned aerial vehicles by emphasizing dynamic features such as speed and heading. However, this approach tends to neglect crucial spatial information, making accurate discrimination of unmanned aerial vehicle characteristics challenging. Furthermore, training methods for situations with imbalanced data among classes have not been proposed by traditional machine learning techniques. In this paper, we propose a data processing method that preserves angle information while maintaining positional details, enabling the deep learning model to better comprehend positional information of drones. Additionally, we introduce a training technique to address the issue of data imbalance.

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References

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