Optimized impedance mismatch through an inverse algorithm applied to a metasurface for subsurface imaging applications – METINVERSE

Electromagnetic characterization of the near subsoil suffers from a weak coupling between the antennas and the air-ground interface. Most of the wave radiated by the transmitting antenna is immediately reflected by the interface and therefore provides no information on the heterogeneities of the subsurface. To reduce the reflection at the interface and achieve a significant signal-to-noise ratio at the receiving antenna, some works have emerged in the last decade around the study of two-dimensional metamaterials. Commonly called metasurfaces (MTS), they are positioned between the antennas and the air-ground interface in order to achieve a higher transmission coefficient. It can be maximized by optimizing the pattern of the unit cells itself. MTS also have the advantages of light weight, ease of fabrication for microwave applications, and good adaptability. Nevertheless, the currently proposed MTS have difficulties in processing a broadband signal and suffer from being a unique-cell structure, so there is always a balance to find between efficiency, adaptability and manufacturability. That’s why current approaches mainly focus on active structures, directive antennas, with beam monitoring and wavefront engineering, complicating the engineering process. This project focuses on a passive layer, which is easier to manufacture and therefore industrialise. In order to address the gap, our main methodological asset is to amplify the electromagnetic coupling at the air-ground interface, thanks to an inverse algorithm. We apply this inverse algorithm directly to the MTS geometry and constitutive parameters in order to make it versatile enough to work in any desired frequency range. Ultimately, the algorithm will help to make the MTS easier to design with no time-consuming process, by imposing simple geometries. This work thus combines optimisation algorithms and metasurfaces in a new way, enabling more efficient engineering of imaging systems in general.