High Resolution Automotive Radar Imaging Integrating Doppler Division Multiple Access and Frequency Agility

doi:10.12142/ZTECOM.202603007

ZTE Communications ›› 2026, Vol. 24 ›› Issue (3): 48-58.DOI: 10.12142/ZTECOM.202603007

• Technology Frontiers • Previous Articles Next Articles

High Resolution Automotive Radar Imaging Integrating Doppler Division Multiple Access and Frequency Agility

Zhang Wei¹(), Zhang Chenyong², Wang Yu², Ding Jin¹, Li Yao²

^1.School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
^2.Chengdu Nanoradar Technology Co. , Ltd. , Chengdu 610041, China

Received:2024-10-24 Online:2026-08-25 Published:2026-09-20
About author:Zhang Wei (zhw5282411@uestc.edu.cn) received his BS, MS, and PhD degrees in electrical engineering from Southwest Jiaotong University, China and the University of Electronic Science and Technology of China (UESTC), in 2004, 2008, and 2013, respectively. He is currently a professor with UESTC. His research interests mainly include array signal processing, millimeter-wave radar, automotive radar, space-time adaptive processing (STAP), and MIMO radar signal processing.
Zhang Chenyong received his MS degree in electronics and communication engineering from the University of Electronic Science and Technology of China. He is currently a radar signal processing engineer. His research interests include the research and development of millimeter-wave radar and phased array radar systems. His main work involves radar target detection, space-time adaptive processing, and FPGA real-time implementation for radar signal processing.
Wang Yu received his bachelor’s and master’s degrees from the University of Electronic Science and Technology of China in 2013 and 2016, respectively. He has been engaged in theoretical research and engineering implementation of millimeter-wave radar detection and imaging technology. His current research interests mainly include millimeter-wave radar signal processing, high-precision detection and imaging algorithms, and their related engineering applications.
Ding Jin received her BS degree in electronic information from the School of Physics in 2022 and MS degree in communication engineering from the School of Information and Communication Engineering in 2025, both from the University of Electronic Science and Technology of China. Her research interests include automotive 4D millimeter-wave radar, point cloud and image fusion.
Li Yao received his MS degree from the University of Electronic Science and Technology of China. He is now an engineer with Chengdu Nanoradar Technology Co., Ltd. His research interests cover millimeter-wave radar signal processing and point cloud processing.
Supported by:
the National Natural Science Foundation of China(62371093);the National Natural Science Foundation of China(62231006)

Abstract

Abstract:

Millimeter-wave (MMW) radar is one of the indispensable sensors for advanced driver assistance systems (ADASs) and autonomous driving. This paper adopts inter-pulse frequency agility (FA) to synthesize a broadband signal, achieving broadband imaging without increasing the sampling rate. Meanwhile, given that Doppler division multiple access (DDMA) has higher transmission efficiency than time division multiple access (TDMA) and is widely used in automotive radar, this paper proposes a signal transmission framework that integrates DDMA and FA. Simulation results demonstrate that the proposed DDMA FA multiple-input multiple-output (DDMA-FA-MIMO) processing architecture can yield 30 to 40 times more detection points for a single target compared to traditional methods, preliminarily achieving target contour imaging.

Key words: automotive radar, radar imaging, stepped frequency radar, 4D radar, DDMA-FA-MIMO

Zhang Wei, Zhang Chenyong, Wang Yu, Ding Jin, Li Yao. High Resolution Automotive Radar Imaging Integrating Doppler Division Multiple Access and Frequency Agility[J]. ZTE Communications, 2026, 24(3): 48-58.

Figures/Tables 8

Figure 1 Automotive radar target detection

Figure 2 Signal transmission scheme integrating DDMA and FA

Figure 3 Range-Doppler matrix of a slow-moving target withthe traditional DDMA modulation (N=6)

Figure 4 Diagram of signal processing

Figure 5 Range-Doppler spectra of typical scenarios for FA FMCW signals

Figure 6 Range-Doppler spectrum and top-view imaging ofthe proposed MIMO radar approach

Figure 7 Comparison of target imaging performance betweentraditional method and DDMA-FA-MIMO approach

Figure 8 Field test results of practical radar system

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High Resolution Automotive Radar Imaging Integrating Doppler Division Multiple Access and Frequency Agility

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