涡旋电磁波雷达平动旋转目标三维微动参数提取方法

袁航 何其芳 罗迎 王志浩 张群

袁航, 何其芳, 罗迎, 等. 涡旋电磁波雷达平动旋转目标三维微动参数提取方法[J]. 雷达学报, 2023, 12(4): 804–816. doi: 10.12000/JR23065
引用本文: 袁航, 何其芳, 罗迎, 等. 涡旋电磁波雷达平动旋转目标三维微动参数提取方法[J]. 雷达学报, 2023, 12(4): 804–816. doi: 10.12000/JR23065
YUAN Hang, HE Qifang, LUO Ying, et al. Three-dimensional micro-motion parameters extraction of translational rotating targets based on vortex electromagnetic wave radar[J]. Journal of Radars, 2023, 12(4): 804–816. doi: 10.12000/JR23065
Citation: YUAN Hang, HE Qifang, LUO Ying, et al. Three-dimensional micro-motion parameters extraction of translational rotating targets based on vortex electromagnetic wave radar[J]. Journal of Radars, 2023, 12(4): 804–816. doi: 10.12000/JR23065

涡旋电磁波雷达平动旋转目标三维微动参数提取方法

doi: 10.12000/JR23065
基金项目: 国家自然科学基金(61971434, 62131020)
详细信息
    作者简介:

    袁 航,博士生,主要研究方向为雷达成像及微多普勒效应

    何其芳,助理工程师,主要研究方向为雷达目标识别、目标情报处理与应用

    罗 迎,教授,博士生导师,主要研究方向为雷达成像、雷达目标识别

    王志浩,博士生,主要研究方向为雷达目标微多普勒效应与目标识别

    张 群,教授,博士生导师,主要研究方向为雷达成像、雷达目标识别

    通讯作者:

    罗迎 luoying2002521@163.com

  • 责任主编:郭忠义 Corresponding Editor: GUO Zhongyi
  • 中图分类号: TN957

Three-dimensional Micro-motion Parameters Extraction of Translational Rotating Targets Based on Vortex Electromagnetic Wave Radar

Funds: The National Natural Science Foundation of China (61971434, 62131020)
More Information
  • 摘要: 与传统平面电磁波雷达相比,涡旋电磁波雷达能同时观测到目标投影到雷达径向和垂直于径向平面的微动分量,可为目标识别提供更多信息。当前关于涡旋电磁波雷达微多普勒效应的研究尚处于起步阶段,初步实现了对旋转目标的三维微动参数的提取,但均未考虑目标平动的影响。因此,该文研究了涡旋电磁波雷达中平动旋转目标的微多普勒效应,推导了平动旋转目标的角多普勒性质,提出了基于1/4微动周期多普勒频移曲线的三维微动参数提取方法,获得了目标旋转频率、旋转半径、旋转矢量和平动速度矢量等参数。仿真验证了角多普勒性质的正确性和参数提取方法的有效性。

     

  • 图  1  平动旋转目标观测模型

    Figure  1.  Observation model of translational rotating targets

    图  2  三维旋转结果

    Figure  2.  The three-dimensional rotation result

    图  3  q在平面${XOY}$上的轨迹

    Figure  3.  The trajectory of the point q on plane ${XOY}$

    图  4  角多普勒频移曲线

    Figure  4.  Angular Doppler frequency shift curve

    图  5  多数情况下的角多普勒频移曲线

    Figure  5.  Angle Doppler curve in most cases

    图  6  4种情况下的角多普勒频移曲线

    Figure  6.  Angle Doppler curve in four cases

    图  7  算法流程图

    Figure  7.  Algorithm flow chart

    图  8  多普勒曲线

    Figure  8.  The curve of Doppler

    图  9  俯仰角及贝塞尔函数值变化曲线

    Figure  9.  Pitch angle and Bessel function value change curve

    图  10  回波时频图(线多普勒+角多普勒)

    Figure  10.  Echo time-frequency map (linear Doppler+ angular Doppler)

    图  11  不同微动参数倍数下的角多普勒曲线

    Figure  11.  Angular Doppler curves under different micro motion parameter multiples

    图  12  不同阶导数下的线多普勒曲线

    Figure  12.  Linear Doppler curve under different order derivatives

    图  13  1/4周期的多普勒频移曲线

    Figure  13.  Doppler frequency shift curve at quarter cycle

    图  14  添加误差后的角多普勒曲线

    Figure  14.  Angular Doppler curve after adding error

    表  1  雷达和目标参数

    Table  1.   Parameters of radar and target

    参数数值
    载频(GHz)10
    阵列半径(m)1
    模态数4
    旋转半径(m)0.4
    旋转频率(Hz)10
    欧拉角(rad)(1.0472,0.7854,0)
    旋转矢量(0.707,–0.612,0.353)
    旋转中心(m)(0.8,1,100)
    速度矢量(m/s)(–10, –5, 10)
    下载: 导出CSV

    表  2  选取点的时刻和角多普勒值

    Table  2.   The time and angular Doppler value of the selected point

    序号时刻(s)角多普勒(Hz)
    104.8271
    20.01336.1418
    30.02678.5308
    40.040012.2020
    50.05349.2937
    60.0667–9.3425
    70.0800–5.6511
    80.09344.6931
    下载: 导出CSV

    表  3  求解过程的迭代误差

    Table  3.   Iterative error in the solving process

    迭代次数误差学习率
    12571.630.01
    2555.7840.001
    3214.9321
    4110.27610
    579.9721
    659.73860.1
    715.3650.01
    89.638351
    95.242740.1
    100.9942690.01
    110.0050360.001
    125.25×10–70.0001
    135.26×10–1510–5
    下载: 导出CSV

    表  4  多元非线性方程组求解结果

    Table  4.   Solution results of multivariate nonlinear equations

    参数估计值理想值
    欧拉角(rad)(1.047,0.785)(1.0472,0.7854)
    旋转半径相对大小(m)0.6310.4
    旋转中心相对大小(m)(1.26,1.57)(0.8,1)
    速度矢量相对大小(m/s)(–15.79, –7.89)(–10, –5)
    下载: 导出CSV

    表  5  完整周期频移曲线下的微动参数估计结果

    Table  5.   Estimation results of micro-motion parameters under complete periodic frequency shift curve

    参数估计值理想值误差
    旋转矢量(0.707,–0.612,0.353)(0.707,–0.612,0.353)0.04%
    旋转频率9.944 Hz10 Hz0.56%
    旋转半径0.398 m0.4 m0.50%
    旋转中心(0.796,0.995) m(0.8,1) m2.75%
    速度矢量(–9.953, –4.976) m/s(–10, –5) m/s0.46%
    下载: 导出CSV

    表  6  选取1/4周期内8个点的时刻和角多普勒值

    Table  6.   Select the time and angular Doppler Values of 8 points within a quarter cycle

    序号时刻(s)角多普勒(Hz)
    10.00104.9123
    20.00435.2019
    30.00765.5134
    40.01105.8640
    50.01436.2706
    60.01766.7500
    70.02107.3187
    80.02437.9918
    下载: 导出CSV

    表  7  1/4周期多元非线性方程组求解结果

    Table  7.   Solution results of multivariate nonlinear equations under 1/4 period

    参数估计值理想值
    欧拉角(rad)(1.047,0.785)(1.0472,0.7854)
    旋转半径相对大小(m)0.0680.4
    旋转中心相对大小(m)(0.136,0.171)(0.8,1)
    速度矢量相对大小(m/s)(–1.709, –0.854)(–10, –5)
    下载: 导出CSV

    表  8  1/4周期频移曲线下的微动参数估计结果

    Table  8.   Estimation results of micro-motion parameters at quarter periodic frequency shift curve

    参数估计值理想值误差
    旋转矢量(0.707,–0.612,0.353) m(0.707,–0.612,0.353) m0.04%
    旋转频率9.944 Hz10 Hz0.56%
    旋转半径0.398 m0.4 m0.50%
    旋转中心(0.796,0.995) m(0.8,1) m2.75%
    速度矢量(–9.953, –4.976) m/s(–10, –5) m/s0.46%
    下载: 导出CSV

    表  9  添加误差后6个点的时刻和角多普勒值

    Table  9.   Time and angle Doppler values of 6 points after adding error

    序号时刻(s)角多普勒(Hz)误差(%)
    10.00033.887819.93
    20.01705.451018.01
    30.03379.234111.79
    40.050411.46511.48
    50.0670–8.79598.84
    60.0837–2.174311.49
    下载: 导出CSV

    表  10  添加误差后的微动参数估计结果

    Table  10.   Estimation results of micro-motion parameters after adding errors

    参数估计值理想值误差
    旋转矢量(0.760, –0.583, 0.271) m(0.707, –0.612, 0.353) m12.36%
    旋转频率9.944 Hz10 Hz0.56%
    旋转半径0.389 m0.4 m2.62%
    旋转中心(0.71,1.02) m(0.8,1) m6.36%
    速度矢量(–9.00, –6.02) m/s(–10, –5) m/s15.18%
    下载: 导出CSV
  • [1] 陈小龙, 关键, 何友. 微多普勒理论在海面目标检测中的应用及展望[J]. 雷达学报, 2013, 2(1): 123–134. doi: 10.3724/SP.J.1300.2012.20102

    CHEN Xiaolong, GUAN Jian, and HE You. Applications and prospect of micro-motion theory in the detection of sea surface target[J]. Journal of Radars, 2013, 2(1): 123–134. doi: 10.3724/SP.J.1300.2012.20102
    [2] LIU Yingxi, ZHANG Qun, LIU Zhidong, et al. An anti-jamming method against interrupted sampling repeater jamming based on compressed sensing[J]. Sensors, 2022, 22(6): 2239. doi: 10.3390/s22062239
    [3] XIONG Shichao, NI Jiacheng, ZHANG Qun, et al. Ground moving target imaging for highly squint SAR by modified minimum entropy algorithm and spectrum rotation[J]. Remote Sensing, 2021, 13(21): 4373. doi: 10.3390/rs13214373
    [4] WANG Haobo, LI Kaiming, LU Xiaofei, et al. ISAR resolution enhancement method exploiting generative adversarial network[J]. Remote Sensing, 2022, 14(5): 1291. doi: 10.3390/rs14051291
    [5] 郭忠义, 汪彦哲, 王运来, 等. 涡旋电磁波旋转多普勒效应研究进展[J]. 雷达学报, 2021, 10(5): 725–739. doi: 10.12000/JR21109

    GUO Zhongyi, WANG Yanzhe, WANG Yunlai, et al. Research advances on the rotational Doppler effect of vortex electromagnetic waves[J]. Journal of Radars, 2021, 10(5): 725–739. doi: 10.12000/JR21109
    [6] WANG Zhihao, LUO Ying, LI Kaiming, et al. Micro-Doppler parameters extraction of precession cone-shaped targets based on rotating antenna[J]. Remote Sensing, 2022, 14(11): 2549. doi: 10.3390/rs14112549
    [7] WANG Zhihao, CHEN Yijun, YUAN Hang, et al. Real micro-Doppler parameters extraction of spinning targets based on rotating interference antenna[J]. Remote Sensing, 2022, 14(21): 5300. doi: 10.3390/rs14215300
    [8] TIAN Xudong, BAI Xueru, and ZHOU Feng. Recognition of micro-motion space targets based on attention-augmented cross-modal feature fusion recognition network[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5104909. doi: 10.1109/TGRS.2023.3275991
    [9] ZHOU Xuening, BAI Xueru, WANG Li, et al. Robust ISAR target recognition based on ADRISAR-net[J]. IEEE Transactions on Aerospace and Electronic Systems, 2022, 58(6): 5494–5505. doi: 10.1109/TAES.2022.3174826
    [10] BAI Xueru, HUI Ye, WANG Li, et al. Radar-based human gait recognition using dual-channel deep convolutional neural network[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(12): 9767–9778. doi: 10.1109/TGRS.2019.2929096
    [11] CHEN Xuebin, YE Chunmao, WANG Yong, et al. Unambiguous estimation of multidimensional parameters for space precession targets with wideband radar measurements[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5112716. doi: 10.1109/TGRS.2022.3168326
    [12] 张群, 胡健, 罗迎, 等. 微动目标雷达特征提取、成像与识别研究进展[J]. 雷达学报, 2018, 7(5): 531–547. doi: 10.12000/JR18049

    ZHANG Qun, HU Jian, LUO Ying, et al. Research progresses in radar feature extraction, imaging, and recognition of target with micro-motions[J]. Journal of Radars, 2018, 7(5): 531–547. doi: 10.12000/JR18049
    [13] 罗迎, 龚逸帅, 陈怡君, 等. 基于跟踪脉冲的MIMO雷达多目标微动特征提取[J]. 雷达学报, 2018, 7(5): 575–584. doi: 10.12000/JR18035

    LUO Ying, GONG Yishuai, CHEN Yijun, et al. Multi-target micro-motion feature extraction based on tracking pulses in MIMO radar[J]. Journal of Radars, 2018, 7(5): 575–584. doi: 10.12000/JR18035
    [14] XU Xuguang and FENG Cunqian. Micro-Doppler extraction of radar targets with translational motion based on spatial transformer network[J]. IEEE Signal Processing Letters, 2022, 29: 2348–2352. doi: 10.1109/LSP.2022.3217411
    [15] GHALEB A, VIGNAUD L, and NICOLAS J M. Micro-Doppler analysis of pedestrians in ISAR imaging[C]. 2008 IEEE Radar Conference, Rome, Italy, 2008: 1–5.
    [16] YUAN Hang, CHEN YiJun, LUO Ying, et al. A resolution-improved imaging algorithm based on uniform circular array[J]. IEEE Antennas and Wireless Propagation Letters, 2022, 21(3): 461–465. doi: 10.1109/LAWP.2021.3135806
    [17] LIU Kang, CHENG Yongqiang, LI Xiang, et al. Passive OAM-based radar imaging with single-in-multiple-out mode[J]. IEEE Microwave and Wireless Components Letters, 2018, 28(9): 840–842. doi: 10.1109/LMWC.2018.2852146
    [18] LIU Kang, CHENG Yongqiang, GAO Yue, et al. Super-resolution radar imaging based on experimental OAM beams[J]. Applied Physics Letters, 2017, 110(16): 164102. doi: 10.1063/1.4981253
    [19] LUO Ying, CHEN Yijun, ZHU Yongzhong, et al. Doppler effect and micro-Doppler effect of vortex-electromagnetic-wave-based radar[J]. IET Radar, Sonar & Navigation, 2020, 14(1): 2–9. doi: 10.1049/iet-rsn.2019.0124
    [20] YUAN Hang, LUO Ying, CHEN Yijun, et al. Micro-motion parameter extraction of rotating target based on vortex electromagnetic wave radar[J]. IET Radar, Sonar & Navigation, 2021, 15(12): 1594–1606. doi: 10.1049/rsn2.12149
    [21] WANG Yu, LIU Kang, LIU Hongyan, et al. Detection of rotational object in arbitrary position using vortex electromagnetic waves[J]. IEEE Sensors Journal, 2021, 21(4): 4989–4994. doi: 10.1109/JSEN.2020.3032665
    [22] WU Zhenxiang, ZHOU Tong, LI Lei, et al. A new modified efficient Levenberg-Marquardt method for solving systems of nonlinear equations[J]. Mathematical Problems in Engineering, 2021, 2021: 5608195. doi: 10.1155/2021/5608195
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出版历程
  • 收稿日期:  2023-04-28
  • 修回日期:  2023-06-28
  • 网络出版日期:  2023-07-17
  • 刊出日期:  2023-08-28

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