论文标题
使用生成模型的圆形极化Fabry-Perot腔传感天线设计
Circularly Polarized Fabry-Perot Cavity Sensing Antenna Design using Generative Model
论文作者
论文摘要
我们考虑设计用于S波段传感应用（例如卫星导航和通信）的圆两极化的Fabry-P'erot腔（FPC）天线的问题。 FPC部分反映表面（PRS）的单位细胞的外围粗糙度的空间分布是重要的设计优化标准。但是，使用全波求解器对每个候选设计的评估在计算上是昂贵的。为此，我们提出了一个深层生成的对抗网络（GAN），以实现一个替代模型，该模型通过投入输出对天线设计及其相应模式进行了训练。使用GAN框架，我们快速评估了大量候选设计的特征，并选择轴向比为0.4 dB，增益为7.5 dB和带宽269 MHz的天线设计。
We consider the problem of designing a circularly polarized Fabry-P'erot cavity (FPC) antenna for S-band sensing applications such as satellite navigation and communication. The spatial distribution of peripheral roughness of the unit cell of FPC's partially reflecting surface (PRS) serves as an important design optimization criterion. However, the evaluation of each candidate design using a full-wave solver is computationally expensive. To this end, we propose a deep generative adversarial network (GAN) for realizing a surrogate model that is trained with input-output pairs of antenna designs and their corresponding patterns. Using the GAN framework, we quickly evaluate the characteristics of a large volume of candidate designs and choose the antenna design with an axial ratio of 0.4 dB, a gain of 7.5 dB, and a bandwidth of 269 MHz.
