Standardized Automated Testing of Frequency Selective Surfaces

We propose the design and implementation of a Standardized Automated Testing of Frequency Selective Surfaces (SAT FSS) platform which will consist of a single piece of equipment that will transmit and receive the RF or Microwave signals with the use of horn antennas. The frequency selective surface (FSS) will be placed in an aperture of a screen surrounded by absorbing tiles which will be in between the receiving and transmitting antennas. The automation will come in the movement of the receiving antenna on a 2D array and the data collection as the equipment takes and records the measurements. In addition to being automated, our proposed platform will also deploy Machine Learning (ML) through the use of a Kriging Surrogate Model to drastically reduce the time required to characterize a FSS. These measurements will then be sent to a cloud-based system for further processing. Our product will be designed to obtain very precise measurements while being extremely efficient and being in a reasonable price range so it can satisfy the needs of an extensive amount of markets. The limitation of our project would be to acquire and save these data precisely for researchers and companies to make the best use of it.