Low-Complexity High-Resolution Parameter Estimation for Automotive MIMO Radars

• Main Authors: Yu-Chien Lin, Ta-Sung Lee, Yun-Han Pan, Kuan-Hen Lin
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: MIMO radar; mmWave radar; CFAR detection; DOA estimation; ESPRIT
• Online Access: https://ieeexplore.ieee.org/document/8753573/

In this paper, we propose a parameter estimation method for multiple-input-multiple-output (MIMO) automotive radars that consists of two stages. The first stage is a low-complexity three-dimensional (3D) constant false alarm rate (CFAR) detection technique that exploits spatial filtering to extend radar coverage, and it performs low-complexity peak detection. The second stage is an ESPRIT-based direction-of-arrival (DOA) estimation technique that adopts time-frequency resource division to generate high-quality snapshots and it performs DOA estimation of targets without the knowledge of the target number. Computer simulations reveal that the proposed method achieves the performance of the two-dimensional ordered statistic CFAR (2D OS-CFAR) while having much lower computational complexity, and it offers the higher resolution DOA estimation compared to the conventional MIMO radars.