Channel Measurement and Modeling for Millimeter-Wave Automotive Radar

被引：8

作者：

Wang, Xiyu ^{[1
,2
]}

He, Danping ^{[3
,4
]}

Guan, Ke ^{[3
,4
]}

Duan, Hongyu ^{[3
,4
]}

Dou, Jianwu ^{[1
,2
]}

Abuali, Najah Abed ^{[5
]}

Zhong, Zhangdui ^{[3
,4
]}

机构：

[1] ZTE Corp Ltd, Shenzhen 518057, Peoples R China

[2] State Key Lab Mobile Network & Mobile Multimedia T, Shenzhen 518057, Peoples R China

[3] Beijing Jiaotong Univ, State Key Lab Adv Rail Autonomous Operat, Beijing 100044, Peoples R China

[4] Frontiers Sci Ctr Smart High Speed Railway Syst, Beijing 100044, Peoples R China

[5] United Arab Emirates Univ UAEU, Fac Informat Technol, Al Ain, U Arab Emirates

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2024年 / 25卷 / 03期

基金：

北京市自然科学基金;

关键词：

Autonomous driving; channel measurement; ray-tracing; mmWave radar; hybrid channel model; SCATTERING; 5G;

D O I：

10.1109/TITS.2023.3285948

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Millimeter-wave (mmWave) automotive radar can detect the surrounding environment using highly directional, high-frequency electromagnetic waves. With these advantages, mmWave radar has become an important component of autonomous driving and integrated sensing systems. Designing systems and sensing algorithms requires the application of realistic channel models and simulation. In this paper, the propagation channel is measured, characterized, and modeled for mmWave automotive radar with typical configurations in scenarios. Based on the channel measurements in urban street and expressway environments, ray-tracing (RT) technology is verified for modeling important objects regarding radar cross-section and echo power. A hybrid channel model is proposed by integrating RT with the stochastic modeling of targets and surrounding environments, which significantly improves simulation efficiency and provides more flexibility for virtual tests in various complex environments.

引用

页码：2933 / 2943

页数：11

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