Resonant Frequency Modeling of Coplanar Waveguide Dual-Frequency Antenna Based on Prior Knowledge Gaussian Process

Abstract

Aiming at the problem of Gaussian process machine learning to solve the problem of low efficiency caused by too many samples in the process of antenna modeling, a Gaussian process modeling method based on prior knowledge is proposed. The input sample of the model is the size parameter of the antenna, and the output sample is the difference of the electromagnetic simulation calculation result and the prior knowledge, thus establishing the Gaussian process model. This modeling method is used to model the resonant frequency of the coplanar waveguide feed dual-frequency microstrip antenna, and the error result is ideal. It is shown that the Gaussian process model based on prior knowledge can replace the electromagnetic simulation software, improve the modeling speed, and prove the feasibility of the method.