대한전자공학회논문지TC (Journal of the Institute of Electronics Engineers of Korea TC)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

Particle Swarm Optimization을 이용한 비균일 급전, 비균등 간격의 선형 어레이 설계

Design of a Randomly Excited and Randomly Spaced Linear Array Using the Particle Swarm Optimization

  • 김철복 (경상대학교 전자공학과) ;
  • 장재삼 (경상대학교 공학연구원) ;
  • 이호상 (경상대학교 공학연구원) ;
  • 김재훈 (경상대학교 전자공학과) ;
  • 박승배 (경상대학교 전자공학과) ;
  • 이문수 (경상대학교 전자공학과)
  • Kim, Cheol-Bok (Dept. of Electronic Engineering, Gyeongsang National University) ;
  • Jang, Jae-Sam (Engineering Research Institute, Gyeongsang National University) ;
  • Lee, Ho-Sang (Engineering Research Institute, Gyeongsang National University) ;
  • Kim, Jae-Hoon (Dept. of Electronic Engineering, Gyeongsang National University) ;
  • Park, Seong-Bae (Dept. of Electronic Engineering, Gyeongsang National University) ;
  • Lee, Mun-Soo (Dept. of Electronic Engineering, Gyeongsang National University)
  • 발행 : 2008.11.25
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초록

본 논문에서는 particle swarm optimization (PSO)을 사용하여 가장 낮은 SLL같을 갖거나 가장 좁은 빔폭을 가지는 비균일 급전, 비균등 간격의 선형 어레이를 설계하였다. 어레이 소자의 급전 크기와 급전 소자간의 간격을 조절하기 위해 변수로 지정하였다. 두 가지 변수를 동시에 무작위로 조절하여 빔패턴을 최적화하였다. 빔패턴의 널 포인트를 기준으로 나누어 각각의 사이드로브에 가중치를 부여함으로써 적합도 함수의 성능을 향상시켰고, 이를 이용하여 최적의 빔패턴을 얻을 수 있었다. 이 때, 가중치 값과 빔패턴을 나누는 각은 여러 번의 시도를 통해 얻을 수 있었다. SLL 뿐만 아니라 빔폭까지 고려하기 위해 fitness function에 추가적인 항목 ${\beta}{\times}BW$을 첨가하였다. 이로써, 가장 낮은 SLL값을 갖거나 가장 좁은 빔폭을 갖는 빔패턴을 갖는 어레이를 설계하였다. 10개의 어레이 소자를 이용하여 최적화 하였을 때, 전자는 -43dB의 SLL값과 $32.2^{\circ}$의 빔폭을 가졌고, 후자는 -26dB의 SLL값과 $24.2^{\circ}$의 빔폭을 가졌다.

In this paper, we use particle swarm optimization (PSO) to design a randomly excited and randomly spaced linear array with either the lowest side lobe level (SLL) or the narrowest beamwidth. The positions and the excitation amplitudes of the array elements are considered as variables to be controlled. The beam pattern is optimized by controlling the two variables simultaneously and randomly. The best beam patterns are obtained using PSO in the fitness function where performance is improved by the random assignment of weight coefficients to each angular sector of the beam Pattern. The weight coefficients and angles are obtained through several trial runs. Also, an extra term, ${\beta}{\ast}BW$, is added to the fitness function to account for the beamwidth as well as the SLL. Is produces the best result for the beam pattern with either the lowest SLL or the narrowest beamwidth. In the former case, the SLL and beamwidth are about -43dB and $32.2^{\circ}$, respectively, with only 10 elements. In the latter case, the SLL and beamwidth are about -26dB and $24.2^{\circ}$, respectively.

키워드

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