Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Optimal Hierarchical Design Methodology for AESA Radar Operating Modes of a Fighter

전투기 AESA 레이더 운용모드의 최적 계층구조 설계 방법론

  • Heungseob Kim (Department of Industrial and Systems Engineering, Changwon National University) ;
  • Sungho Kim (Department of Systems Engineering, Korea Air Force Academy) ;
  • Wooseok Jang (Division of Data Analysis, Korea Institute of Science and Technology Information (KISTI)) ;
  • Hyeonju Seol (School of Integrated National Security, Chungnam National University)
  • 김흥섭 (창원대학교 산업시스템공학과) ;
  • 김성호 (공군사관학교 시스템공학과) ;
  • 장우석 (한국과학기술정보연구원(KISTI) 데이터분석본부) ;
  • 설현주 (충남대학교 국가안보융합학부)
  • Received : 2023.11.16
  • Accepted : 2023.12.07
  • Published : 2023.12.31
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Abstract

This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS's rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment.

Keywords

Acknowledgement

This research was supported by Changwon National University in 2023~2024.

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