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

Marco Antonio Pumallica-Paro, Jorge Luis Arizaca-Cusicuna, Mark Clemente-Arenas

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2019 9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas316-321
Número de páginas6
ISBN (versión digital)9781728105666
DOI
EstadoPublicada - set. 2019
Publicado de forma externa
Evento9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019 - Granada, Espana
Duración: 9 set. 201913 set. 2019

Serie de la publicación

NombreProceedings of the 2019 9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019

Conferencia

Conferencia9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019
País/TerritorioEspana
CiudadGranada
Período9/09/1913/09/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

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