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Review

An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications

1
School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
2
PanoSim Technology Limited Company, Jiaxing 314000, China
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(11), 3310; https://doi.org/10.3390/s24113310
Submission received: 6 April 2024 / Revised: 7 May 2024 / Accepted: 16 May 2024 / Published: 22 May 2024
(This article belongs to the Special Issue Recent Advances of FMCW-Based Radar Sensors)

Abstract

Autonomous driving technology is considered the trend of future transportation. Millimeter-wave radar, with its ability for long-distance detection and all-weather operation, is a key sensor for autonomous driving. The development of various technologies in autonomous driving relies on extensive simulation testing, wherein simulating the output of real radar through radar models plays a crucial role. Currently, there are numerous distinctive radar modeling methods. To facilitate the better application and development of radar modeling methods, this study first analyzes the mechanism of radar detection and the interference factors it faces, to clarify the content of modeling and the key factors influencing modeling quality. Then, based on the actual application requirements, key indicators for measuring radar model performance are proposed. Furthermore, a comprehensive introduction is provided to various radar modeling techniques, along with the principles and relevant research progress. The advantages and disadvantages of these modeling methods are evaluated to determine their characteristics. Lastly, considering the development trends of autonomous driving technology, the future direction of radar modeling techniques is analyzed. Through the above content, this paper provides useful references and assistance for the development and application of radar modeling methods.
Keywords: millimeter-wave radar; radar modeling; autonomous driving; ray tracing; machine learning millimeter-wave radar; radar modeling; autonomous driving; ray tracing; machine learning

Share and Cite

MDPI and ACS Style

Huang, K.; Ding, J.; Deng, W. An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications. Sensors 2024, 24, 3310. https://doi.org/10.3390/s24113310

AMA Style

Huang K, Ding J, Deng W. An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications. Sensors. 2024; 24(11):3310. https://doi.org/10.3390/s24113310

Chicago/Turabian Style

Huang, Kaibo, Juan Ding, and Weiwen Deng. 2024. "An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications" Sensors 24, no. 11: 3310. https://doi.org/10.3390/s24113310

APA Style

Huang, K., Ding, J., & Deng, W. (2024). An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications. Sensors, 24(11), 3310. https://doi.org/10.3390/s24113310

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