  The 4D millimeter-wave (mmWave) radar, proficient in measuring the range,
azimuth, elevation, and velocity of targets, has attracted considerable
interest within the autonomous driving community. This is attributed to its
robustness in extreme environments and the velocity and elevation measurement
capabilities. However, despite the rapid advancement in research related to its
sensing theory and application, there is a conspicuous absence of comprehensive
surveys on the subject of 4D mmWave radar. In an effort to bridge this gap and
stimulate future research, this paper presents an exhaustive survey on the
utilization of 4D mmWave radar in autonomous driving. Initially, the paper
provides reviews on the theoretical background and progress of 4D mmWave
radars, encompassing aspects such as the signal processing workflow, resolution
improvement approaches, and extrinsic calibration process. Learning-based radar
data quality improvement methods are present following. Then, this paper
introduces relevant datasets and application algorithms in autonomous driving
perception, localization and mapping tasks. Finally, this paper concludes by
forecasting future trends in the realm of 4D mmWave radar in autonomous
driving. To the best of our knowledge, this is the first survey specifically
dedicated to the 4D mmWave radar in autonomous driving.
