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디지털 지형 고도 데이터를 이용한 자동 지형 추종 시뮬레이터 개발

Development of Automatic Terrain Following Simulator Using Digital Terrain Elevation Data

  • 이지수 (한국항공대학교 스마트항공모빌리티학과) ;
  • 유문규 (한국항공대학교 스마트항공모빌리티학과) ;
  • 이현주 (한국항공대학교 스마트항공모빌리티학과) ;
  • 송기훈 (국방과학연구소) ;
  • 전동익 (모멘텀스페이스(주)) ;
  • 이상철 (한국항공대학교 스마트항공모빌리티학과)
  • Jisu Lee (Department of Smart Air Mobility, Korea Aerospace University) ;
  • MunGyou Yoo (Department of Smart Air Mobility, Korea Aerospace University) ;
  • Hyunju Lee (Department of Smart Air Mobility, Korea Aerospace University) ;
  • Ki Hoon Song (Agency for Defense Development) ;
  • Dong-Ik Cheon (Momentum Space Co.Ltd) ;
  • Sangchul Lee (Department of Smart Air Mobility, Korea Aerospace University)
  • 투고 : 2023.11.21
  • 심사 : 2024.01.11
  • 발행 : 2024.02.28

초록

본 논문에서는 디지털 지형 고도 데이터를 이용한 자동 지형 추종 시뮬레이터를 제안하였다. ATF Simulator는 Flight Simulator, Radar Simulator, TFC Simulator로 구성하였다. 지형 추종에 필요한 지형 정보로 디지털 지형 고도 데이터와 디지털 지형 고도 데이터를 이용하여 생성한 레이다 스캔 데이터를 활용하였다. ATF Simulator는 디지털 지형 고도 데이터를 이용하는 Passive mode, 레이다 스캔 데이터를 이용하는 Active mode, 두 가지 모두 이용하는 Hybrid mode로 세 가지 운용모드를 제공한다. LabVIEW 개발 환경과 MATLAB App Designer 개발 환경을 통해 지형 추종 시스템 개발에 소요되는 비용 및 시간을 줄일 수 있는 ATF Simulator를 개발하였으며 기능요구사항을 충족하는지 확인하여 검증하였다.

In this paper, an Automatic Terrain Following (ATF) Simulator using Digital Terrain Elevation Data (DTED) was proposed. This ATF Simulator consists of a Flight Simulator, a Radar Simulator, and a Terrain Following Computer (TFC) Simulator. DTED and radar scan data generated with DTED were used as the terrain information necessary for terrain following. The ATF Simulator provides three modes of operation: a passive mode that uses DTED, an active mode that uses radar scan data, and a hybrid mode that uses both. We developed an ATF Simulator that could reduce the cost and time required to develop a terrain following system using the LabVIEW development environment and the MATLAB App Designer development environment. It was verified by confirming that the ATF Simulator met all functional requirements.

키워드

과제정보

본 연구는 2023년도 한화시스템(주)의 재원을 지원받아 수행되었습니다(No. 202015011).

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