Antenna Shape Modeling based on Histogram of Oriented Gradients Feature

Abstract

A least square support vector machine (SVM) model is proposed for shape modeling of slot antennas. The slot image is mapped into the electromagnetic response by the SVM model. A modified shape-changing technique is also proposed to describe the antenna geometry by the quadratic uniform B-spline curve and generate the slot images. In the model, the histogram of oriented gradients feature is extracted from the slot images to show the appearance and shape of the slot. The relationship between the histogram of oriented gradient features and the electromagnetic responses is preliminarily built on SVM and the transfer function. Then a radial basis function network is used for error correction. The effectiveness of the proposed model is confirmed with an example of a tri-band microstrip-fed slot antenna. Compared with the convolutional neural network (CNN), the feature extracted by CNN is substituted by the histogram of oriented gradients feature, and the proposed model shows the same accuracy and the improvement of training efficiency.