Mutual Interference Mitigation of Millimeter-Wave Radar Based on Variational Mode Decomposition and Signal Reconstruction

被引:11
作者
Li, Yanbing [1 ]
Feng, Bo [2 ]
Zhang, Weichuan [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[2] Beijing Inst Radio Measurement, Beijing 100854, Peoples R China
[3] Griffith Univ, Inst Integrated & Intelligent Syst, Nathan, Qld 4111, Australia
关键词
frequency modulated continuous wave; interference mitigation; millimeter-wave radar; signal reconstruction; variational mode decomposition; VEHICLES; SYSTEMS;
D O I
10.3390/rs15030557
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As an important remote sensing technology, millimeter-wave radar is used for environmental sensing in many fields due to its advantages of all-day, all-weather operation. With the increasing use of radars, inter-radar interference becomes increasingly critical. Severe mutual interference degrades radar signal quality and affects the performance of post-processing, e.g., synthetic aperture radar (SAR) imaging and target tracking. Aiming to deal with mutual interference, we propose an interference mitigation method based on variational mode decomposition (VMD). With the characteristics that the target is a single-frequency sine wave and the interference is a broadband signal, VMD is used for decomposing the radar received signal and separating the target from the interference. Interference mitigation is then implemented in each decomposed mode, and an interference-free signal is obtained through the reconstruction process. Simulation results of multi-target scenarios demonstrate that the proposed method outperforms existing decomposition-based methods. This conclusion is also confirmed by the experimental results on real data.
引用
收藏
页数:24
相关论文
共 42 条
  • [1] Interference in Automotive Radar Systems Characteristics, mitigation techniques, and current and future research
    Allond, Stephen
    Stark, Wayne
    Ali, Murtaza
    Hegde, Manju
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 2019, 36 (05) : 45 - 59
  • [2] The Rise of Radar for Autonomous Vehicles Signal processing solutions and future research directions
    Bilik, Igal
    Longman, Oren
    Villeval, Shahar
    Tabrikian, Joseph
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 2019, 36 (05) : 20 - 31
  • [3] Mutual interference of millimeter-wave radar systems
    Brooker, Graham M.
    [J]. IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 2007, 49 (01) : 170 - 181
  • [4] A PARAMETER-ESTIMATION APPROACH TO ESTIMATION OF FREQUENCIES OF SINUSOIDS
    CHAN, YT
    LAVOIE, JMM
    PLANT, JB
    [J]. IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1981, 29 (02): : 214 - 219
  • [5] Chatzitheodoridi M.E., 2020, P 2020 IEEE RADAR C, P1, DOI [10.1109/RadarConf2043947.2020.9266564, DOI 10.1109/RADARCONF2043947.2020.9266564]
  • [6] Radio Frequency Interference Mitigation in High-Frequency Surface Wave Radar Based on CEMD
    Chen, Zezong
    Xie, Fei
    Zhao, Chen
    He, Chao
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 14 (05) : 764 - 768
  • [7] Minimum Integrated Sidelobe Ratio Filters for MIMO Radar
    Davis, Michael S.
    Lanterman, Aaron D.
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2015, 51 (01) : 405 - 416
  • [8] On the Potential of Empirical Mode Decomposition for RFI Mitigation in Microwave Radiometry
    Diez-Garcia, Raul
    Camps, Adriano
    Park, Hyuk
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [9] Pursuing Drones With Drones Using Millimeter Wave Radar
    Dogru, Sedat
    Marques, Lino
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2020, 5 (03) : 4156 - 4163
  • [10] Variational Mode Decomposition
    Dragomiretskiy, Konstantin
    Zosso, Dominique
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (03) : 531 - 544