To extend the antenna design on printed circuit boards (PCBs) for more engineers of interest, we propose a simple method that models PCB antennas with a few basic components. By taking two separate steps to decide their geometric dimensions and positions, antenna prototypes can be facilitated with no experience required. Random sampling statistics relate to the quality of dimensions are used in selecting among dimension candidates. A novel image-based classifier using a convolutional neural network (CNN) is introduced to further determine the positions of these fixed-dimension components. Two examples from wearable products have been chosen to examine the entire workflow. Their final designs are realistic and their performance metrics are not inferior to the ones designed by experienced engineers.

我们提出了一种简单的方法，使用几个基本组件来模拟PCB天线的设计。通过分别决定其几何尺寸和位置，即使无需经验也可以方便地生成天线原型。我们引入了基于卷积神经网络（CNN）的新型基于图像的分类器，进一步确定这些固定尺寸组件的位置。我们选取了两个可穿戴产品的例子来检查整个工作流程，它们的最终设计是真实的，并且性能指标不逊于经验工程师设计的天线。

基于图像分类器的平面天线设计生成方法