AI-Based 3D Antenna Pattern Reconstruction

In this paper, we address the challenge of reconstructing full 3D antenna radiation patterns from limited data scenarios, a task essential yet often constrained by resource and data availability. We present a novel deep learning approach, utilizing a pretrained model to accurately estimate 3D patterns from azimuthal and elevation slices alone. Our approach demonstrates significant advancements over traditional analytical methods, offering a robust solution capable of handling a wide variety of antenna types and configurations. The model's performance has been rigorously evaluated against a diverse set of antennas, achieving impressive results in terms of efficiency and accuracy. The implications of this work for antenna analysis and design are profound, offering a quick and reliable method for pattern reconstruction.