Angular Super-Resolution for Target Positioning Using Dual-Antenna Dielectric Radar

High angle resolution is commonly achieved by utilizing a wide aperture for electromagnetic systems, such as radar, navigator, sonar, and communication systems. Especially for radars, a multiple-input multiple-output (MIMO) scheme has been widely used to extend the aperture via a virtual array. Meanwhile, machine learning or metasurfaces have been widely researched to improve the resolution during the last few years. These approaches either require multiple antennas with strict arrangement or involve intricate optimizations. In this paper, we propose a novel framework for an elegant dual-antenna radar system with dielectric radome, which gets inspiration from dielectric penetrating radar imaging, to realize angular super resolution for target positioning. The dual-antenna radar model is rigorously derived and the position or angle estimation is formulated in theory. It proves to obtain excellent performance in multi-target positioning and angular discrimination through only two independent radars that are placed with flexible spacing. We test the position estimation performance on automotive millimeter-wave radars, and the proposed method shows great advantages compared with many other super-resolution methods, revealing great potential in fields like automatic driving.