Machine Learning-Aided Design of Dielectric-Filled Slotted Waveguide Antennas With Specified Sidelobe Levels

This paper presents the use of machine learning (ML) to facilitate the design of dielectric-filled Slotted Waveguide Antennas (SWAs) with specified sidelobe level ratios (SLR). Conventional design methods for air-filled SWAs require the simultaneous solving of complex equations to deduce the antenna’s design parameters, which typically requires further manual simulation-based optimization to reach the desired...