基于RD-ANM的毫米波雷达动目标超分辨DOA估计方法

舒月 傅东宁 陈展野 黄岩 张彦君 谭晓衡 陶俊

舒月, 傅东宁, 陈展野, 等. 基于RD-ANM的毫米波雷达动目标超分辨DOA估计方法[J]. 雷达学报, 2023, 12(5): 986–999. doi: 10.12000/JR23040
引用本文: 舒月, 傅东宁, 陈展野, 等. 基于RD-ANM的毫米波雷达动目标超分辨DOA估计方法[J]. 雷达学报, 2023, 12(5): 986–999. doi: 10.12000/JR23040
SHU Yue, FU Dongning, CHEN Zhanye, et al. Super-resolution DOA estimation method for a moving target equipped with a millimeter-wave radar based on RD-ANM[J]. Journal of Radars, 2023, 12(5): 986–999. doi: 10.12000/JR23040
Citation: SHU Yue, FU Dongning, CHEN Zhanye, et al. Super-resolution DOA estimation method for a moving target equipped with a millimeter-wave radar based on RD-ANM[J]. Journal of Radars, 2023, 12(5): 986–999. doi: 10.12000/JR23040

基于RD-ANM的毫米波雷达动目标超分辨DOA估计方法

doi: 10.12000/JR23040
基金项目: 国家自然科学基金(62001062, 62271142, 61901112)
详细信息
    作者简介:

    舒 月,博士生,主要研究方向为毫米波雷达DOA估计

    傅东宁,博士,主要研究方向为雷达动目标检测、雷达射频仿真

    陈展野,博士,副教授,主要研究方向为雷达动目标检测、阵列信号处理、雷达仿真

    黄 岩,博士,副教授,主要研究方向为雷达抗干扰、毫米波雷达信号处理

    张彦君,博士生,主要研究方向为DOA估计、阵列信号处理

    谭晓衡,博士,教授,主要研究方向为阵列信号处理、通信信号处理

    陶 俊,博士,教授,主要研究方向为水声信号处理

    通讯作者:

    陈展野 xdczy@hotmail.com

    黄岩 yellowstone0636@hotmail.com

  • 责任主编:杨明磊 Corresponding Editor: YANG Minglei
  • 中图分类号: TN957

Super-resolution DOA Estimation Method for a Moving Target Equipped with a Millimeter-wave Radar Based on RD-ANM

Funds: The National Natural Science Foundation of China (62001062, 62271142, 61901112)
More Information
  • 摘要: 超分辨波达方位角估计是车载毫米波雷达实现目标精准定位及跟踪需要解决的关键问题。针对车载场景中常见的阵列孔径受限、少快拍、低信噪比以及信源相干的情况,该文提出了一种基于距离多普勒域原子范数最小化(RD-ANM)的车载毫米波雷达动目标超分辨DOA估计方法:首先,构建了基于动目标雷达回波的距离多普勒域阵列接收信号;其次,设计了动目标多普勒耦合相位补偿矢量,用以削弱目标运动对DOA估计的影响;最后,提出了基于原子范数框架的多目标超分辨DOA估计方法。相较于车载毫米波雷达现使用的DOA估计算法,该文算法能够在基于低信噪比条件和单快拍处理前提下获得较高的测角分辨率和估计精度,以及拥有不牺牲阵列孔径对相干信号进行处理的稳健性能。理论分析、数值仿真以及实测实验验证了该文算法的有效性。

     

  • 图  1  车载TDM-MIMO毫米波雷达探测场景示意图

    Figure  1.  Schematic diagram of vehicle borne TDM-MIMO MMW radar detection scene

    图  2  距离向和多普勒向的2D-DFT处理示意图

    Figure  2.  Schematic diagram of range dimension DFT and Doppler dimension DFT

    图  3  目标与阵列相对位置示意图

    Figure  3.  Schematic diagram of relative position between target and array

    图  4  RD域-MUSIC及RD域-FBSS MUSIC对相干信源的处理

    Figure  4.  RD-MUSIC’s and RD-FBSS MUSIC’s processing of coherent sources

    图  5  计算复杂度

    Figure  5.  Computational complexity

    图  6  目标检测

    Figure  6.  Target detection

    图  7  耦合多普勒相位对RD域-DOA估计的影响

    Figure  7.  Effect of coupled Doppler phase on RD-DOA estimation

    图  8  大角度间隔下的RD域-DOA估计结果

    Figure  8.  RD-DOA estimation results at large angle intervals

    图  9  大角度间隔下的信噪比-均方根误差图

    Figure  9.  SNR-RMSE diagram at large angle intervals

    图  10  大角度间隔下的蒙特卡罗独立重复实验

    Figure  10.  Monte Carlo independent repetition experiment at large angle intervals

    图  11  小角度间隔下的蒙特卡罗独立重复实验

    Figure  11.  Monte Carlo independent repetition experiment at small angle intervals

    图  12  可分辨相干目标数

    Figure  12.  Number of resolvable coherent targets

    图  13  实测场景

    Figure  13.  Practical scene

    图  14  实测1、实测2 DOA估计示意图

    Figure  14.  Schematic diagrame of DOA estimation for test 1 and 2

    表  1  实验仿真参数

    Table  1.   The simulation parameters

    参数数值参数数值
    MIMO$3{T}_{{\rm{x}}}4{R}_{{\rm{x}}}$发射功率9.48 dBm
    CPI数1发射天线增益23 dBi
    载频77 GHz接收天线增益34 dBi
    有效带宽150 MHz最小可检测信噪比10 dB
    Chirp重复周期10 μs系统损耗3 dB
    Chirp数256接收机噪声系数10 dB
    ADC采样率25.6 MSPS接收机带宽4 GHz
    ADC采样点数256后向散射系数10 dBsm
    下载: 导出CSV

    表  2  目标参数

    Table  2.   Target parameter

    参数数值
    (相对初始距离,相对运动速度)(50 m, 10 m/s)
    (距离解算值,速度解算值)(50 m, 9.8925 m/s)
    下载: 导出CSV

    表  3  实测DOA估计结果

    Table  3.   DOA estimation results based on practical data

    组别设置参数实测结果
    轴向/径向距离(m)速度(m/s)角度(推演值)(°)距离(m)速度(m/s)角度(实测值)(°)
    1(4.296, –0.3/0.05)0(–3.9946, 0.6668)4.10160(–4.1, 0.3)
    2(4.296, 0.35/0.5)0(0, 6.6386)4.29690(0.7, 6)
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-03-31
  • 修回日期:  2023-05-20
  • 网络出版日期:  2023-06-12
  • 刊出日期:  2023-10-28

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