A Multiobjective Genetic Algorithm for Analysis, Design and Optimization of Antipodal Vivaldi Antennas

被引：0
|
作者：
Antonio Pumallica-Paro, Marco [1 ]
Luis Arizaca-Cusicuna, Jorge [1 ]
Clemente-Arenas, Mark [2 ]
机构：
[1] Univ Nacl San Antonio Abad Cusco, Escuela Profes Ingn Elect, Cuzco, Peru
[2] Univ Nacl Ingn INICTEL UNI, Inst Nacl Invest & Capacitac Telecomunicac, DIDT, Grp Radio Frecuencia Microondas & Opt G RFMO, Av San Luis 1771, Lima 41, Peru
来源：
PROCEEDINGS OF THE 2019 9TH IEEE-APS TOPICAL CONFERENCE ON ANTENNAS AND PROPAGATION IN WIRELESS COMMUNICATIONS (IEEE APWC' 19) | 2019年
关键词：
Multi-Objective Genetic Algorithm; Antipodal Vivaldi Antennas; Ground Penetrating Radar;
D O I：
10.1109/apwc.2019.8870420
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In the this contribution, a Multi-Objective Genetic Algorithm (MOGA) was implemented to analyze, design and optimize several Antipodal Vivaldi Antennas (AVA) that are being used on Ground Penetration Radars (GPR) applications. This algorithm was implemented and used as an optimization tool in a commercial available software. Directivity, lower cutoff frequency (LCF), bandwidth and cross-polarization were the objectives to be optimized. For the use of the MOGA, the 3D model of the antenna is built in the simulator. Some of its parameters are defined as variables, as the dimensions and shape of the antenna (Individual) depend on the value that its parameters (Genes) take. This work proves to be simple and time saving tool to optimize parameters in a geometry changing system as GPR.
引用
收藏
页码：316 / 321
页数：6
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