Computational Microwave Localization and Material Identification Using Conformal Metasurface Antennas
This paper presents a simple and compact microwave sensing approach using conformal frequency-diverse metasurfaces to jointly localize and identify materials within a pipe. The frequency-diverse metasurfaces consist of an electrically large SIW patterned with metamaterial radiators with diverse resonant frequencies. These antennas can generate spatially distinct patterns that can encode information into simple frequency sweeps. Two such antennas are wrapped around a pipe to localize and identify objects inside, thereby replacing large, complex tomographic antenna arrays with simple frequency sweeps. To do that, a sensing matrix is experimentally populated using targets made of different materials placed in a grid of possible locations. Using computational processing, we show that the system successfully distinguishes among metal, wood, and nylon rods and accurately localizes their positions using unique frequency signatures. The extension of this method to two-object localization is examined. The results highlight a simple, low-cost, and reliable framework for microwave sensing that enables material characterization and localization without large arrays, scanning, or complex hardware.