Design and Analysis of Ku/K-band Circular SIW Patch Antenna using 3D EM-based Artificial Neural Networks

Abstract

Substrate Integrated Waveguide (SIW) antennas are considered as main radiators for RF and microwave wireless systems due to their low profile, low cost and soft integration with the other devices. The gain of a SIW patch antenna may be enhanced using different techniques such as Artificial Neural Networks (ANN) by modifying the antenna’s geometry with high efficiency comparing to electromagnetic techniques that take more time. This paper describes a novel structure of a circular SIW patch antenna design using a tree-dimensional electromagnetic (3D-EM) simulation based on ANN model which is developed as an accurate tool for synthesizing the forward side and then analyzing the reverse side of the problem. In this work, ANN algorithms are used for training the samples to provide precise geometrical dimensions of the SIW patch antenna with high accuracy for the target requirements. The antenna is designed to operate in Ku and K frequency bands, resonate at 16.10 GHz and 19.81 GHz respectively and show good performance resulting in low return losses of less than -10dB to -29dB for the selective frequency bands.