Analysis of Coaxial Microstrip Patch Antenna using Artificial Neural Network

This paper presents an artificial intelligence-based neurocomputational analysis technique for microstrip patch antennas (MPA) having versatile satellite frequency bands. MPAs are widely researched for their planar design and application in rockets and satellites. Analyzing, designing, and optimizing MPAs is complex due to numerous configuration-dependent geometric parameters, since it is the basic element of a massive array. So, AI-based approaches are increasingly popular among researchers for enhancing MPA analysis, design, and optimization. The proposed antenna has three variable parameters like rectangular radiating patch of width $\left(W_{p}\right)$, length $\left(L_{p}\right)$, and feed location (F). Rest of the parameters like substrate of dielectric coefficient $\epsilon_{r}$, height, and thickness of copper patch are constant.