Volume 11 Issue 5
Oct.  2022
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HE Zishu, CHENG Ziyang, LI Jun, et al. A survey of collocated MIMO radar[J]. Journal of Radars, 2022, 11(5): 805–829. doi: 10.12000/JR22128
Citation: HE Zishu, CHENG Ziyang, LI Jun, et al. A survey of collocated MIMO radar[J]. Journal of Radars, 2022, 11(5): 805–829. doi: 10.12000/JR22128
shu

A Survey of Collocated MIMO Radar

DOI: 10.12000/JR22128

  • School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Funds:  The National Natural Science Foundation of China (62001084, 62031007)
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  • Corresponding author: CHENG Ziyang, zycheng@uestc.edu.cn
  • Received Date: 2022-06-29
  • Accepted Date: 2022-07-27
  • Rev Recd Date: 2022-07-27
    • Available Online: 2022-07-29
  • Publish Date: 2022-08-18
    Abstract
  • As a novel radar system, the Multiple-Input Multiple-Output (MIMO) radar with waveform diversity has demonstrated excellent performance in several aspects, including target detection, parameter estimation, radio frequency stealth, and anti-jamming characteristics. After nearly 20 years of in-depth research by scholars, the MIMO radar theory based on orthogonal waveforms has significantly improved. It has been widely applied in fields such as automobile-assisted driving and safety defense. In recent years, with the introduction of the concepts of electromagnetic environment perception and knowledge aid, and the application requirements of radar-active anti-jamming, radio frequency stealth, and detection-communication integration, multiple new theories and methods have been generated for the MIMO radar in system architecture, transmit waveform design, and signal processing. This paper aims to review and summarize the research works on MIMO radar published in the past 20 years, including: the principle of the orthogonal-waveform MIMO radar, its target detection performance analysis and typical applications; waveform design and characteristics of the orthogonal-waveform MIMO radar; knowledge-aided cognitive MIMO waveform design and algorithm; MIMO detection-communication integrated waveform design and algorithm; MIMO radar parameter estimation; MIMO radar target detection; and MIMO radar resource management and scheduling. Finally, the paper discusses the clutter suppression and Space-Time Adaptive Processing (STAP) of MIMO radar in airborne applications, the signal processing of MIMO radar in imaging, and the signal processing of chirp millimeter-wave (mmWave) MIMO radar based on time division multi-waveform diversity.

     

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