Social Network Optimization Based Procedure for Beam-Scanning Reflectarray Antenna Design

被引：14
|
作者：
Niccolai, Alessandro [1 ]
Beccaria, Michele [2 ]
Zich, Riccardo E. [1 ]
Massaccesi, Andrea [2 ]
Pirinoli, Paola [2 ,3 ]
机构：
[1] Politecn Milan, Dipartimento Energia, I-20156 Milan, Italy
[2] Politecn Torino, Dipartimento Elettron & Telecomunicaz, I-10129 Turin, Italy
[3] Natl Res Council Italy, Ist Elettron & Ingn Informaz & Telecomunicaz, I-10129 Turin, Italy
来源：
IEEE OPEN JOURNAL OF ANTENNAS AND PROPAGATION | 2020年 / 1卷
关键词：
Social network optimization; beam-scanning reflectarray; optimization environment; evolutionary optimization; PARTICLE SWARM OPTIMIZATION; PATTERN SYNTHESIS; HYBRID TAGUCHI; ARRAY; ALGORITHM; CELLS;
D O I：
10.1109/OJAP.2020.3022935
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Evolutionary algorithms can be successfully exploited for carrying on an effective design of beam-scanning passive reflectarrays, even if the problem is highly non-linear and multimodal. In this article, the Social Network Optimization (SNO) algorithm has been used for assessing an effective design procedure of a beam-scanning passive reflectarray (RA). For exploiting at most the optimization capabilities of SNO, the entire optimization environment has been deeply analyzed in all its parts. The performance of SNO and the beam-scanning capabilities of the optimized RA have been assessed through the comparison with other well established Evolutionary Algorithms.
引用
收藏
页码：500 / 512
页数：13
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