Design Optimization of Ultra-Wideband Vivaldi Antenna using Artificial Intelligence

In this work, computationally efficient design optimization of frequency selective surface (FSS)-loaded ultra-wideband Vivaldi antenna via the use data-driven surrogate model is studied. The proposed methodology consists a multi-layer FSS structure aimed for performance improvement design, which makes multi-objective multi-dimensional problem. For having fast and accurate process, alongside metaheuristic optimizer honeybee mating (HBMO) had been used. optimally designed prototyped its characteristics measured. obtained experimental results are compared with simulated method. Results show that FSS-loaded has enhanced directivity without structure, any losses in return loss characteristics. operates at 2–12 GHz band maximum gain 10 dBi good solution RADAR applications.