Neural network modeling for the fast estimation of superstrate loading effect on rectangular microstrip patch antennas

Abstract

A neural network model for the shift in resonant frequency of a rectangular microstrip antenna covered with a dielectric layer is presented. The primary effect of such loading is to change the resonant frequency of the antenna. The absolute value of change increases with operating frequency, relative permittivity and the thickness of the dielectric layer. This change may cause degradation in performance due to the inherently narrow bandwidth of microstrip antennas, if the effect of loading is not considered in the design. The neural network model presented here may be used to design microstrip antennas that may be subjected to icing or other atmospheric deposition or coated with protective layers. The model developed is found to be in good agreement with electromagnetic simulation using method of moments.