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2025-09-15
Deep-Learning-Driven Ultra-Broadband X-Band Reflectarray Antenna via Physics-Guided Synthesis
By
Progress In Electromagnetics Research C, Vol. 159, 273-280, 2025
Abstract
We present an eight-page in-depth study of a single-layer broadband reflectarray antenna operating over the 8 GHz to 12 GHz X-band. The array employs a dual-ring hex-slit unit cell and a physics-informed deep-learning (DL) surrogate model that reduces geometry optimisation time by ×120 compared with brute-force sweeps. The 30 cm × 30 cm prototype comprises 273 passive elements, delivers a 530° reflection-phase span, 27 dB peak gain, 56% aperture efficiency and 34.6 dB cross-polar discrimination. A residual network trained on 5000 HFSS datapoints predicts reflection phase with 0.9° MAE, whereas its inverse sibling outputs element radii in 10 ms. CST full-wave simulations and a preliminary S-parameter measurement corroborate the synthesis accuracy to within 0.25 dB. Comprehensive parametric, angular-stability and computational analyses provide guidance for extending DL-assisted reflectarrays to higher frequencies and reconfigurable architectures.
Citation
Mohammadjavad Zakeri, and Sajjad Sadeghi, "Deep-Learning-Driven Ultra-Broadband X-Band Reflectarray Antenna via Physics-Guided Synthesis," Progress In Electromagnetics Research C, Vol. 159, 273-280, 2025.
doi:10.2528/PIERC25071302
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