Performance evaluation of 2D vs 4D surrogate models of reflectarray unit cells based on support vector regression

  1. Rodriguez Prado, Daniel 1
  2. López Fernández, Jesús Alberto 1
  3. Arrebola Baena, Manuel 1
  1. 1 Group of Signal Theory and Communications, Universidad de Oviedo
Actas:
15th European Conference on Antennas and Propagation (EuCAP)

Año de publicación: 2021

Congreso: European Conference on Antennas and Propagation, EuCAP 2021 (15th. 2021. Düsseldorf, Germany)

Tipo: Aportación congreso

GOOGLE SCHOLAR lock_openRUO editor

Resumen

Surrogate models of reflectarray unit cells are usually generated employing a number of input variables such as geometrical features of the cell, frequency and angles of incidence. Here we show how surrogate models based on support vector regression can be improved by removing their dependence on the angle of incidence. This is done by grouping the reflectarray elements under a relatively small set of incidence angles. Thus, instead of generating models with the angles of incidence as input variables, models are obtained per angle of incidence pair, reducing dimensionality to improve their performance without significant impact on the reflectarray analysis accuracy.

€ Ver financiación

Información de financiación

This work was supported in part by the Ministerio de Ciencia, Innovación y Universidades under projects TEC2017-86619-R (ARTEINE) and IJC2018-035696-I; by the Ministerio de Economía, Industria y Competitividad under project TEC2016-75103-C2-1-R (MYRADA); by the Gobierno del Principado de Asturias/FEDER under Project GRUPIN-IDI/2018/000191.

Financiadores

  • Ministerio de Ciencia, Innovación y Universidades Spain
    • TEC2017-86619-R
  • Ministerio de Ciencia, Innovación y Universidades Spain
    • IJC2018-035696-I
  • Gobierno del Principado de Asturias Spain
    • GRUPIN-IDI/2018/000191
  • Ministerio de Economía y Competitividad Spain
    • TEC2016-75103-C2-1-R