基于变分模态分解与优选的超高分辨ISAR成像微多普勒抑制方法

李中余 桂亮 海宇 武俊杰 王党卫 王安乐 杨建宇

李中余, 桂亮, 海宇, 等. 基于变分模态分解与优选的超高分辨ISAR成像微多普勒抑制方法[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24043
引用本文: 李中余, 桂亮, 海宇, 等. 基于变分模态分解与优选的超高分辨ISAR成像微多普勒抑制方法[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24043
LI Zhongyu, GUI Liang, HAI Yu, et al. Ultrahigh-resolution ISAR micro-Doppler suppression methodology based on variational mode decomposition and mode optimization[J]. Journal of Radars, in press. doi: 10.12000/JR24043
Citation: LI Zhongyu, GUI Liang, HAI Yu, et al. Ultrahigh-resolution ISAR micro-Doppler suppression methodology based on variational mode decomposition and mode optimization[J]. Journal of Radars, in press. doi: 10.12000/JR24043

基于变分模态分解与优选的超高分辨ISAR成像微多普勒抑制方法

doi: 10.12000/JR24043
基金项目: 国家自然科学基金(62171084),衢州市财政资助科研项目(2022D014)
详细信息
    作者简介:

    李中余,教授,博士生导师,研究方向为新体制雷达成像技术等

    桂 亮,硕士生,研究方向为逆合成孔径雷达成像及雷达微多普勒效应等

    海 宇,博士生,研究方向为超高分辨率雷达成像、微波光子雷达成像、稀疏信号恢复等

    武俊杰,教授,博士生导师,研究方向为合成孔径雷达成像、双/多基合成孔径雷达、雷达信号处理等

    王党卫,教授,研究方向为新体制雷达与信号处理等

    王安乐,副教授,研究方向为微波光子雷达等

    杨建宇,教授,博士生导师,研究方向为雷达信号处理、合成孔径雷达成像等

    通讯作者:

    李中余 zhongyu_li@uestc.edu.cn

    桂亮 lianggui46@qq.com

  • 责任主编:罗迎 Corresponding Editor: LUO Ying
  • 中图分类号: TN957

Ultrahigh-resolution ISAR Micro-Doppler Suppression Methodology Based on Variational Mode Decomposition and Mode Optimization

Funds: The National Natural Science Foundation of China (62171084), The Municipal Government of Quzhou (2022D014)
More Information
  • 摘要: 逆合成孔径雷达(ISAR)在对空中目标成像时,目标自身的转动、振动等局部微动将产生微多普勒效应,回波将附加额外的多普勒调制,造成频谱展宽。在超高分辨条件下,这一微动特性将会影响主体散射点的聚焦,导致目标图像局部散焦模糊,严重影响成像质量。并且,微多普勒相位还具有时变非平稳特性,难以从ISAR目标回波中准确估计或分离出微多普勒。为了解决上述问题,该文利用目标主体回波和微多普勒分量的时频分布差异,提出一种基于变分模态分解(VMD)与优选的非参数化方法抑制了回波中的微多普勒分量,消除了微多普勒对成像的影响,获得超高分辨率的无人机ISAR成像结果。该文首先引入VMD算法并将其扩展到复数域,将ISAR目标回波数据沿方位向分解为若干个中心频率均匀分布于多普勒采样带宽中的模函数,在此基础上利用图像熵指标优化分解参数和筛选成像模态,以保证微多普勒的良好抑制和主体回波的较完整保留。与现有基于经验模态分解(EMD)和局部均值分解(LMD)的方法相比,所提方法在超大带宽条件下对旋翼微动引起的微多普勒干扰有着更为出色的抑制效果,而且对机身部分的保留更为完整。最后,通过仿真对比和超宽带微波光子ISAR无人机实测数据处理,证明了该文所提方法的有效性和优势。

     

  • 图  1  几种典型目标所占距离门数目随信号带宽的变化

    Figure  1.  Variation of the number of range cells for several typical targets with bandwidth

    图  2  ISAR转台模型

    Figure  2.  Turntable model of ISAR

    图  3  含微动部件目标的ISAR几何模型

    Figure  3.  ISAR geometric model of targets with micro-motion components

    图  4  微多普勒信号的STFT谱和频谱图

    Figure  4.  STFT spectrogram and spectrum of the micro-Doppler signal

    图  5  扩展VMD原理示意图

    Figure  5.  Schematic diagram of the extended VMD

    图  6  所提微多普勒抑制方法流程图

    Figure  6.  Flow diagram of the proposed micro-Doppler suppression method

    图  7  多点目标布局及直接成像图

    Figure  7.  Multi-point target layout and direct imaging diagram

    图  8  各种算法处理后的成像结果对比

    Figure  8.  Comparison of the imaging results processed by various algorithms

    图  9  各种算法处理后的STFT谱对比

    Figure  9.  Comparison of the STFT spectrogram processed by various algorithms

    图  10  不同信噪比下的仿真成像结果对比

    Figure  10.  Comparison of simulated imaging results at different SNR

    图  11  成像场景及目标示意图

    Figure  11.  Radar system and target diagram

    图  12  各种算法处理无人机数据的成像结果对比

    Figure  12.  Comparison of the effects of different algorithms on the processing of measured data

    图  13  处理后旋翼中心点对应方位STFT谱

    Figure  13.  STFT spectrogram of the center point on the rotor after processing

    图  14  旋翼中心点残余相位与方位剖面对比图

    Figure  14.  Azimuth residual phase and profile comparison of the center point on the rotor

    表  1  仿真参数表

    Table  1.   Simulation parameter table

    参数 数值
    载波频率${f_{\mathrm{c}}}$ 35 GHz
    信号带宽${B_{\mathrm{r}}}$ 10 GHz
    脉冲重复频率${\text{PRF}}$ 833 Hz
    成像积累时间 2.46 s
    无人机运动速度 5 m/s
    目标俯仰角 15°
    旋翼个数 4
    单旋翼叶片个数 2
    叶片长度l 0.1 m
    单叶片微动散射点个数 5
    旋翼转速${\omega _{\mathrm{r}}}$ 20$\pi $ rad/s
    下载: 导出CSV

    表  2  各种算法处理后的图像质量比较

    Table  2.   Comparison of image quality processed by various algorithms

    算法 能量相似比(区域1) 能量相似比(区域2) 图像熵 对比度 锐度
    直接成像 8.64 3.87 8.84 18.65 1.03E+10
    PGA 9.60 4.11 8.75 20.19 9.54E+09
    基于EMD 0.22 1.23 8.31 21.44 8.72E+09
    基于LMD 0.16 0.84 8.28 20.45 8.58E+09
    本文方法 0.15 0.16 8.16 22.71 9.15E+09
    下载: 导出CSV

    表  3  六旋翼无人机实测实验参数表

    Table  3.   Experimental parameter table for the hexacopter UAV

    参数 数值
    载波频率${f_{\mathrm{c}}}$ 35 GHz
    信号带宽${B_{\mathrm{r}}}$ 10 GHz
    脉冲重复频率${\text{PRF}}$ 833 Hz
    成像积累时间 0.72 s
    目标俯仰角 15°
    下载: 导出CSV

    表  4  六旋翼无人机成像质量比较

    Table  4.   Comparison of imaging quality of the hexacopter

    算法 图像熵 对比度 锐度
    直接成像 8.19 22.12 5.44E+11
    PGA 7.98 23.59 2.90E+11
    基于EMD 7.63 23.28 4.17E+11
    基于LMD 7.59 23.14 4.11E+11
    基于CVMD 7.67 23.66 4.05E+11
    本文方法 7.05 25.79 4.33E+11
    下载: 导出CSV

    表  5  不同算法的运算复杂度

    Table  5.   Computational complexity of different algorithms

    算法 运算复杂度
    本文算法 $O(MNK{L_1}{L_2}{\log _2}M)$,${L_1}$为VMD循环次数,${L_2}$为差分进化迭代次数
    基于LMD[23] $O(MN{L_3}{L_4})$,${L_3}$为调频信号迭代次数,${L_4}$为子信号分离次数
    基于EMD[20] $O(MN{L_5}{L_6})$,${L_5}$为EMD循环次数,${L_6}$为复信号投影维度数
    PGA[29] $O(M{L_7}{\log _2}M + MN{L_7})$,${L_7}$为PGA迭代次数
    下载: 导出CSV
  • [1] 保铮, 邢孟道, 王彤. 雷达成像技术[M]. 北京: 电子工业出版社, 2005: 239–241.

    BAO Zheng, XING Mengdao, and WANG Tong. Radar Imaging Techniques[M]. Beijing: Publishing House of Electronics Industry, 2005: 239–241.
    [2] 李源. 逆合成孔径雷达理论与对抗[M]. 北京: 国防工业出版社, 2013: 48–55.

    LI Yuan. Inverse Synthetic Aperture Radar Theory and Confrontation[M]. Beijing: National Defense Industry Press, 2013: 48–55.
    [3] 杨建宇. 雷达技术发展规律和宏观趋势分析[J]. 雷达学报, 2012, 1(1): 19–27. doi: 10.3724/SP.J.1300.2013.20010.

    YANG Jianyu. Development laws and macro trends analysis of radar technology[J]. Journal of Radars, 2012, 1(1): 19–27. doi: 10.3724/SP.J.1300.2013.20010.
    [4] 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.
    [5] LIU Zheng and SUN Huixia. Micro-Doppler analysis and application of radar targets[C]. IEEE International Conference on Information and Automation, Changsha, China, 2008: 1343–1347. doi: 10.1109/ICINFA.2008.4608210.
    [6] 张群, 罗迎, 何劲. 雷达目标微多普勒效应研究概述[J]. 空军工程大学学报: 自然科学版, 2011, 12(2): 22–26. doi: 10.3969/j.issn.1009-3516.2011.02.005.

    ZHANG Qun, LUO Ying, and HE Jin. Overview of research on micro-Doppler effect of radar targets[J]. Journal of Air Force Engineering University: Natural Science Edition, 2011, 12(2): 22–26. doi: 10.3969/j.issn.1009-3516.2011.02.005.
    [7] CHEN V C. Analysis of radar micro-Doppler with time-frequency transform[C]. The 10th IEEE Workshop on Statistical Signal and Array Processing, Pocono Manor, USA, 2000: 463–466. doi: 10.1109/SSAP.2000.870167.
    [8] WANG Anle, ZHENG Daikun, DU Shirui, et al. Microwave photonic radar system with ultra-flexible frequency-domain tunability[J]. Optics Express, 2021, 29(9): 13887–13898. doi: 10.1364/OE.423952.
    [9] LUO Xiong, WANG Anle, WO Jianghai, et al. Microwave photonic video imaging radar with widely tunable bandwidth for monitoring diverse airspace targets[J]. Optics Communications, 2019, 451: 296–300. doi: 10.1016/j.optcom.2019.06.073.
    [10] CHEN V C, TAHMOUSH D, and MICELI W J. Radar Micro-Doppler Signatures: Processing and Applications[M]. Stevenage: The Institution of Engineering and Technology, 2014: 187–225. doi: 10.1049/pbra034e.
    [11] CHEN V C, LI Fayin, HO S S, et al. Micro-Doppler effect in radar: Phenomenon, model, and simulation study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 2–21. doi: 10.1109/TAES.2006.1603402.
    [12] TUSZYNSKI M, WOJTKIEWICZ A, and KLEMBOWSKI W. Bimodal clutter MTI filter for staggered PRF radars[C]. IEEE International Conference on Radar, Arlington, USA, 1990: 176–180. doi: 10.1109/RADAR.1990.201158.
    [13] 万显荣, 谢德强, 易建新, 等. 基于STFT谱图滑窗相消的微动杂波去除方法[J]. 雷达学报, 2022, 11(5): 794–804. doi: 10.12000/JR22157.

    WAN Xianrong, XIE Deqiang, YI Jianxin, et al. Micro-Doppler clutter removal method based on the cancelation of sliding STFT spectrogram[J]. Journal of Radars, 2022, 11(5): 794–804. doi: 10.12000/JR22157.
    [14] WANG Yong, ZHOU Xingyu, LU Xiaofei, et al. An approach of motion compensation and ISAR imaging for micro-motion targets[J]. Journal of Systems Engineering and Electronics, 2021, 32(1): 68–80. doi: 10.23919/JSEE.2021.000008.
    [15] 何其芳, 张群, 罗迎, 等. 正弦调频Fourier-Bessel变换及其在微动目标特征提取中的应用[J]. 雷达学报, 2018, 7(5): 593–601. doi: 10.12000/JR17069.

    HE Qifang, ZHANG Qun, LUO Ying, et al. A sinusoidal frequency modulation Fourier-Bessel transform and its application to micro-Doppler feature extraction[J]. Journal of Radars, 2018, 7(5): 593–601. doi: 10.12000/JR17069.
    [16] 符吉祥, 邢孟道, 徐丹, 等. 一种基于微波光子超高分辨雷达机翼振动参数估计方法[J]. 雷达学报, 2019, 8(2): 232–242. doi: 10.12000/JR19001.

    FU Jixiang, XING Mengdao, XU Dan, et al. Vibration-parameters estimation method for airplane wings based on microwave-photonics ultrahigh-resolution radar[J]. Journal of Radars, 2019, 8(2): 232–242. doi: 10.12000/JR19001.
    [17] STANKOVIC L, DJUROVIC I, and THAYAPARAN T. Separation of target rigid body and micro-Doppler effects in ISAR imaging[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(4): 1496–1506. doi: 10.1109/TAES.2006.314590.
    [18] LI Kaiming, LIANG Xianjiao, ZHANG Qun, et al. Micro-Doppler signature extraction and ISAR imaging for target with micromotion dynamics[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(3): 411–415. doi: 10.1109/LGRS.2010.2081660.
    [19] CHOI I, KANG K, KIM K, et al. Use of ICA to separate micro-Doppler signatures in ISAR images of aircraft that has fast-rotating parts[J]. IEEE Transactions on Aerospace and Electronic Systems, 2022, 58(1): 234–246. doi: 10.1109/TAES.2021.3098110.
    [20] BAI Xueru, XING Mengdao, ZHOU Feng, et al. Imaging of micromotion targets with rotating parts based on empirical-mode decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(11): 3514–3523. doi: 10.1109/TGRS.2008.2002322.
    [21] FLANDRIN P, RILLING G, and GONCALVES P. Empirical mode decomposition as a filter bank[J]. IEEE Signal Processing Letters, 2004, 11(2): 112–114. doi: 10.1109/LSP.2003.821662.
    [22] GAO Yunchao, GE Guangtao, SHENG Zhengyan, et al. Analysis and solution to the mode mixing phenomenon in EMD[C]. International Congress on Image and Signal Processing, Sanya, China, 2008: 223–227. doi: 10.1109/CISP.2008.193.
    [23] YUAN Bin, CHEN Zengping, and XU Shiyou. Micro-Doppler analysis and separation based on complex local mean decomposition for aircraft with fast-rotating parts in ISAR imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(2): 1285–1298. doi: 10.1109/TGRS.2013.2249588.
    [24] DRAGOMIRETSKIY K and ZOSSO D. Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531–544. doi: 10.1109/TSP.2013.2288675.
    [25] 杨利超. 超高分辨ISAR成像技术研究[D]. [博士论文], 西安电子科技大学, 2021. doi: 10.27389/d.cnki.gxadu.2021.000089.

    YANG Lichao. Study on ISAR ultrahigh-resolution imaging techniques[D]. [Ph.D. dissertation], Xidian University, 2021. doi: 10.27389/d.cnki.gxadu.2021.000089.
    [26] 邵帅. 高分辨ISAR成像与精细化运动补偿技术研究[D]. [博士论文], 西安电子科技大学, 2020. doi: 10.27389/d.cnki.gxadu.2020.003431.

    SHAO Shuai. Study on high resolution ISAR imaging and fine motion compensation techniques[D]. [Ph.D. dissertation], Xidian University, 2020. doi: 10.27389/d.cnki.gxadu.2020.003431.
    [27] YANG Degui, LI Jin, LIANG Buge, et al. A multi-rotor drone micro-motion parameter estimation method based on CVMD and SVD[J]. Remote Sensing, 2022, 14(14): 3326. doi: 10.3390/rs14143326.
    [28] DAS S and SUGANTHAN P N. Differential evolution: A survey of the state-of-the-art[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(1): 4–31. doi: 10.1109/TEVC.2010.2059031.
    [29] EICHEL P H and JAKOWATZ C V. Phase-gradient algorithm as an optimal estimator of the phase derivative[J]. Optics Letters, 1989, 14(20): 1101–1103. doi: 10.1364/OL.14.001101.
  • 加载中
图(14) / 表(5)
计量
  • 文章访问数:  366
  • HTML全文浏览量:  51
  • PDF下载量:  35
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-03-20
  • 修回日期:  2024-05-24
  • 网络出版日期:  2024-06-19

目录

    /

    返回文章
    返回