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4D mmWave Radar for Autonomous Driving Perception: A Comprehensive Survey

雷达 感知 计算机科学 遥感 航空学 运输工程 电信 工程类 地理 心理学 神经科学
作者
Lili Fan,Junhao Wang,Yuanmeng Chang,Yuke Li,Yutong Wang,Dongpu Cao
出处
期刊:IEEE transactions on intelligent vehicles [Institute of Electrical and Electronics Engineers]
卷期号:9 (4): 4606-4620 被引量:14
标识
DOI:10.1109/tiv.2024.3380244
摘要

The rapid development of autonomous driving technology has driven continuous innovation in perception systems, with 4D millimeter-wave (mmWave) radar being one of the key sensing devices. Leveraging its all-weather operational characteristics and robust perception capabilities in challenging environments, 4D mmWave radar plays a crucial role in achieving highly automated driving. This review systematically summarizes the latest advancements and key applications of 4D mmWave radar in the field of autonomous driving. To begin with, we introduce the fundamental principles and technical features of 4D mmWave radar, delving into its comprehensive perception capabilities across distance, speed, angle, and time dimensions. Subsequently, we provide a detailed analysis of the performance advantages of 4D mmWave radar compared to other sensors in complex environments. We then discuss the latest developments in target detection and tracking using 4D mmWave radar, along with existing datasets in this domain. Finally, we explore the current technological challenges and future directions. This review offers researchers and engineers a comprehensive understanding of the cutting-edge technology and future development directions of 4D mmWave radar in the context of autonomous driving perception. 4D mmWave radar, autonomous driving, perception, multi-modal fusion, 3D object detection.

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