A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation.

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Publication Details

Published
2024-08-16
DOI
https://doi.org/10.1109/aces-china62474.2024.10699737
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
0.00

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article

A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

Qingsha S. Cheng, Yu Kuang, Juntao Zhang, Ziheng Tian
Engineering Applied Research
article

A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

Qingsha S. Cheng, Yu Kuang, Juntao Zhang, Ziheng Tian
article en

Abstract

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation.

Southern University of Science and Technology (CN)
National Natural Science Foundation of China, Southern University of Science and Technology
Affordable and clean energy
Openalex Percentile: Top 81%
Engineering Applied Research
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