Datos del Documento

Por favor, use este identificador para citar o enlazar este documento: https://ria.asturias.es/RIA/handle/123456789/11933
Título : Support Vector Machines to Accelerate Reflectarray Analysis and Optimization
Autor : Rodriguez Prado, Daniel
López Fernádez, Jesús Alberto
Arrebola Baena, Manuel
Las-Heras Andrés, Fernando
Palabras clave : reflectarray
support vector machine (SVM)
method of moments (MoM)
local periodicity
shaped-beam pattern
Fecha de publicación : abr-2018
Editorial : IET
Citación : D. R. Prado, J. A. López-Fernández, M. Arrebola, F. Las-Heras, "Support vector machines to accelerate reflectarray analysis and optimization", 12th European Confer- ence on Antennas and Propagation (EuCAP), London (UK), 9-13/04/2018
Resumen : The analysis of reflectarray antennas is substantially accelerated by using Support Vector Machines (SVMs) to model the matrix of reflection coefficients in substitution of a full-wave analysis based on local periodicity, the Method of Moments (MoM-LP) in this work. The SVM model takes as input variables two geometrical variables which control the phase-shift for two different polarizations. Thus, the employed model is able to analyze shaped-beam dual-linear polarized reflectarrays. As test case, a shaped-beam reflectarray radiating a pattern for Local Multipoint Distribution Service applications, presenting a squared-cosecant cut in elevation and sectored-beam in azimuth, is presented, showing a high degree of agreement in both the copolar and crosspolar patterns between the simulations of SVM and MoM-LP. Furthermore, the acceleration with regard to the MoM-LP is between three and four orders of magnitude, which demonstrates the suitability of the SVM model approach for reflectarray direct optimization.
URI : https://ria.asturias.es/RIA/handle/123456789/11933
ISBN : 978-1-78561-816-1
Aparece en las colecciones: Ingeniería
Open Access DRIVERset

Archivos en este documento:
Fichero Tamaño Formato  
Archivo.pdf391.65 kBAdobe PDFVer/Abrir
Mostrar el registro Completo

Ver estadísticas del documento

Este documento está sujeto a una licencia Creative Commons: Licencia Creative Commons Creative Commons