MIMO imaging method with iterative-based super-resolution for automotive radar

This paper proposes a MIMO imaging method with an iterative-based super-resolution technique for automotive radar applications. Vehicle radars have recently used 4D imaging radar, offering improved detection ranges and high-resolution capability. The application of imaging radar technology aims to extend the maximum detection distance through noise reduction techniques while also enabling the miniaturization of vehicle radars using the MIMO approach. To enhance the maximum detection distance, we employ a Wavelet-based noise reduction method for range FFT. Additionally, for improved angular resolution, we use a MIMO radar implementation based on a super-resolution algorithm, in contrast to the conventional MIMO imaging method that utilizes the FFT algorithm. Specifically, we focus on an emerging iterative-based algorithm, which effectively addresses the complexity issues associated with super-resolution techniques. Through extensive experiments, we validate the effectiveness of this proposed method. The results demonstrate its potential in realizing wide detection distance and high-resolution for vehicle radar systems.