Metaheuristic Search-Based Design for Reduced Design Time of an AMC Integrated Circularly Polarized Antenna for Air and Space Applications

A surrogate model is used followed by a metaheuristic search engine to reduce the number of simulation iterations. The design consists of an artificial magnetic conductor (AMC) which functions as reflector in conjunction with a monopole radiator, reducing antenna module’s profile and boosting gain. This configuration allows for effective use of the frequency spectrum by enabling closely spaced circularly polarized bands. Precision radar, navigation, and high-speed communication are among the air and space applications that benefit greatly from the antenna design’s exceptional X-band performance. Compared to previously proposed machine learning techniques for antenna optimization, our optimized antenna has a better gain (8.1 and 5.3 dB), dual band with impedance bandwidth 33% (8.6–12 GHz), and larger axial ratio bandwidth of 12.6%, 4.7% (8.9–10.1 GHz, and 11.39–11.95 GHz). The polarization sense of both the bands is LHCP and RHCP, respectively. Both optimization time and the number of electromagnetic (EM) simulations are greatly reduced.