Work

The Gradual Interval Mapping Method Integration Framework for Multiple Metasurfaces Fast Design

Year: 2025

Type: article

Abstract: This work presents a gradual interval mapping method (IMM) integration framework for the rapid design of multiple metasurfaces. By leveraging the deep neural networks, the gradual design framework efficiently predicts both S-parameters and geometric structures using interval folding lines as input. Unlike traditional and current approaches, the proposed method integrates IMM with a filling strategy, simplifying data processing and enhancing prediction accuracy. To validate its effectiveness, three types of frequency selective surface (FSS) are designed, one of which is fabricated and experimentally measured in a microwave chamber. Simulation and measurement results confirm the superior performance of the framework, highlighting its potential for intelligent electromagnetic device design. Finally, we conclude with a short discussion of the work, including its limitations and developability.

Source: IEEE Transactions on Antennas and Propagation

DOI: 10.1109/tap.2025.3632301

Authors: Peng Wang, Chao Luo, Zhenning Li, Wen Jiang, Tao Hong, Gert Frølund Pedersen, Ming Shen

Institutions: Xidian University, Chinese Academy of Sciences, Aerospace Information Research Institute, Aalborg University

Language: English

Topic: Advanced Antenna and Metasurface Technologies

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Natural Science Foundation of China

Awards: G645370642, G8563334474