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Study on Pattern Synthesis of Conformal Array Antenna Using Enhanced Adaptive Genetic Algorithm

향상된 적응형 유전 알고리즘을 이용한 컨포멀 배열 안테나의 빔 합성 연구

  • Seong, Cheol-Min (Department of Radio Science and Engineering, Chungnam National University) ;
  • Lee, Jae-Duk (Department of Radio Science and Engineering, Chungnam National University) ;
  • Han, In-Hee (Microwave Technologies Group) ;
  • Ryu, Hong-Kyun (Agency for Defense Development) ;
  • Lee, Kyu-Song (Agency for Defense Development) ;
  • Park, Dong-Chul (Department of Radio Science and Engineering, Chungnam National University)
  • 성철민 (충남대학교 전자전파정보통신공학과) ;
  • 이재덕 (충남대학교 전자전파정보통신공학과) ;
  • 한인희 (엠티지) ;
  • 류홍균 (국방과학연구소) ;
  • 이규송 (국방과학연구소) ;
  • 박동철 (충남대학교 전자전파정보통신공학과)
  • Received : 2014.01.27
  • Accepted : 2014.03.24
  • Published : 2014.05.31

Abstract

This paper proposes an enhanced adaptive genetic algorithm(EAGA) dedicated to pattern synthesis of array antenna which conforms to a curved surface of rotation with quadratic function. EAGA combines adaptive genetic algorithm(AGA) with invasive weed optimization(IWO) for the faster convergence and the lower cost value of the cost function. The amplitude and phase of each excited weighting factor are optimized to meet the required goals using EAGA. The EAGA results indicate that the proposed algorithm is superior to AGA when applied to the problem of conformal array antenna pattern synthesis.

본 논문에서는 2차 함수 곡선의 회전체 곡면 위에 있는 배열 안테나의 빔 합성을 위한 Enhanced Adaptive Genetic Algorithm(EAGA)을 제안하였다. 제안된 알고리즘은 더 빠른 수렴 속도와 더 낮은 비용함수 값을 얻기 위해 Adaptive Genetic Algorithm(AGA)과 Invasive Weed Optimization(IWO)을 결합시켰다. 각 안테나 소자의 급전 크기와 위상의 최적화된 값은 EAGA를 통해 구하였으며, 이 결과를 통해 EAGA가 컨포멀 배열 안테나의 패턴 합성 알고리즘으로써 AGA보다 더 우수함을 보였다.

Keywords

References

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