Angular Super-Resolution Algorithm for Millimeter-Wave Automotive Radar Based on Virtual Array Augmentation

Accurate spatial localization and classification of targets are crucial for achieving target detection based on millimeter-wave automotive radar. However, the lower angular resolution hinders the perceptual capabilities of radar systems, making it challenging to meet the application requirements in real-world environments. This paper first quantitatively analyzes the impact of angular resolution on the performance of downstream target detection tasks on radar data from real road scenarios. Then a radar angular super-resolution algorithm based on Multiple Input Multiple Output (MIMO) radar virtual receive channel augmentation is proposed, without increasing the complexity and cost of the radar hardware system. Validation on downstream target detection tasks demonstrates that radar virtual receive channel augmentation effectively increases the radar system’s angular resolution, thereby enhancing the performance of downstream target detection tasks.