Preliminary Description of a 2D Near-Field Electromagnetic Imaging Database

With the goal of improving machine learning approaches in inverse scattering, we overview an experimental data set collected with a near-field microwave imaging system. Machine learning approaches often train solely on synthetic data, and one of the reasons for this is that no experimentally-derived public data set exists. The imaging system consists of 24 antennas surrounding the imaging region, connected via a switch to a vector network analyzer. The data set contains over 1000 full Scattering parameter scans of three targets from 3–5 GHz. In this work, we show preliminary results of a direct data-to-image inversion algorithm.