Two-Dimensional NHA-Based Super-Resolution Technique for Millimeter-Wave FMCW Radar With Limited Channels

In recent years, millimeter-wave radar has attracted significant attention for noncontact position estimation in diverse applications, including human monitoring and automotive systems. However, the azimuth resolution of these systems is fundamentally constrained by the number of available channels. The trade-off between detection performance and antenna size complicates system design and increases manufacturing costs, creating a barrier to widespread radar adoption. To address this issue, this study proposes a range-azimuth super-resolution imaging technique for 79 GHz frequency-modulated continuous wave (FMCW) radar based on two-dimensional nonharmonic analysis (2DNHA), which is a frequency analysis method that achieves high-precision line spectrum estimation with minimal dependence on the number of channels. Simulation results for point source targets indicate that, in the single-target scenario, 2DNHA reduces azimuth estimation errors that are lower than those of two-dimensional fast Fourier transform (2DFFT) and comparable to those of ANM, even with a limited number of channels. Its range-azimuth estimation errors asymptotically approach the Cramér–Rao bound in noisy environments. Additionally, in the multiple-target scenario, its range-azimuth maps, featuring a high-precision sparse representation with robustness to the number of channels, demonstrate superior close-target separation and noise resistance compared with conventional methods such as 2DFFT and 2D multiple signal classification. Experimental validation using a metal reflector further confirms that 2DNHA consistently delivers super-resolution imaging. The proposed approach enhances the detection performance of range-azimuth FMCW radars with limited channels, offering a cost-effective and efficient solution for mm-wave radar applications.