基于太赫兹ViSAR的无源干扰物成像

范磊 杨琪 王宏强 易俊

范磊, 杨琪, 王宏强, 等. 基于太赫兹ViSAR的无源干扰物成像[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24174
引用本文: 范磊, 杨琪, 王宏强, 等. 基于太赫兹ViSAR的无源干扰物成像[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR24174
FAN Lei, YANG Qi, WANG Hongqiang, et al. Terahertz-ViSAR-Based imaging of passive jamming objects[J]. Journal of Radars, in press. doi: 10.12000/JR24174
Citation: FAN Lei, YANG Qi, WANG Hongqiang, et al. Terahertz-ViSAR-Based imaging of passive jamming objects[J]. Journal of Radars, in press. doi: 10.12000/JR24174

基于太赫兹ViSAR的无源干扰物成像

DOI: 10.12000/JR24174
基金项目: 国家自然科学基金(62201591,62035014),湖南省科技创新计划项目(2024RC3143)
详细信息
    作者简介:

    范 磊,博士生,主要研究方向为太赫兹雷达系统、太赫兹视频合成孔径雷达成像、动目标指示与精细化成像等

    杨 琪,副教授,博士,主要研究方向为太赫兹雷达系统、空间目标逆合成孔径雷达成像

    王宏强,研究员,博士,主要研究方向为太赫兹雷达、新体制雷达信号处理、雷达目标识别技术

    易 俊,讲师,博士,主要研究方向为太赫兹雷达系统与高灵敏度检测

    通讯作者:

    王宏强 wanghongqiang@nudt.edu.cn

  • 责任主编:丁金闪 Corresponding Editor: DING Jinshan
  • 中图分类号: TN957.91

Terahertz-ViSAR-Based Imaging of Passive Jamming Objects

Funds: The National Natural Science Foundation of China (62201591,62035014), Science and Technology Innovation Program of Hunan Province (2024RC3143)
More Information
  • 摘要: 无源干扰物的成像一直是雷达成像/对抗研究中的热点问题,直接影响着雷达目标检测和识别性能。然而,在微波频段下,为达到期望的方位分辨率,通常需要较长的驻留时间来形成单幅图像,这使得无源干扰物难以通过成像直接区分,并缺乏时间维的分辨能力。相比之下,太赫兹频段成像系统在实现相同方位分辨率时所需的合成孔径更短,从而更容易获得低延迟、高分辨、高帧率的成像结果。因此,太赫兹雷达在视频合成孔径雷达(ViSAR)技术中具有重要潜力。首先,对机载太赫兹ViSAR的孔径划分及其成像系统指标进行简要分析。随后,静止无源干扰物以角反阵和伪装网为例,探索它们运动补偿前后的成像结果及成像特性,并首次实验验证了具有上下起伏网格结构的伪装网在太赫兹频段将表现出粗糙特性,展现出该频段下特殊的目标特性。接下来,运动无源干扰物以旋转角反为例,分析了旋转角反成像所形成的压制性成像干扰。考虑到静止场景在相邻子孔径下类似,在完成帧间成像结果图像和幅度校准后,可直接在图像域内基于非相干相减实现旋转角反检测,从而提取感兴趣信号并实施非参数化补偿。目前关于太赫兹频段下对无源干扰物的外场成像实验验证甚少。本研究开展了太赫兹频段公里级机载外场试验,有效验证了太赫兹ViSAR具备对无源干扰物良好的高分辨与高帧率成像能力。

     

  • 图  1  条带 ViSAR成像场景示意图

    Figure  1.  Diagram of stripmap ViSAR imaging

    图  2  两种孔径划分方式示意图

    Figure  2.  Diagram of two ways of aperture division

    图  3  整体处理框架

    Figure  3.  Overall processing framework

    图  4  基于相邻帧间图像的旋转角反检测

    Figure  4.  Detection of rotating reflectors based on adjacent frames

    图  5  太赫兹条带 ViSAR实验场景示意图

    Figure  5.  Diagram of airborne experiments regarding stripmap terahertz ViSAR

    图  6  机场场景下 3组实验目标的光学照片

    Figure  6.  Optical photos of three experimental targets in the airport

    图  7  实际机载飞行状态

    Figure  7.  Practical airborne flying status

    图  8  角反阵与伪装网的运动补偿前后的 3帧成像结果

    Figure  8.  Imaging results of corner reflector array and camouflage mat

    图  9  角反阵运动补偿前后结果对比

    Figure  9.  Local zoom-in images and contour plots of corner reflector array before and after MOCO

    图  10  距离与方位剖面图

    Figure  10.  Range and azimuth profiles

    图  11  伪装网在运动补偿前后的局部图以及 2.5D重构图

    Figure  11.  Zoom-in images of camouflage mat before and after MOCO

    图  12  关于旋转角反的连续三帧整体成像结果

    Figure  12.  Three consecutive frames of scene containing rotating reflector

    图  13  旋转角反的三帧局部放大图

    Figure  13.  Local zoom-in images of rotating reflectors under three frames

    图  14  帧 #2 下两个旋转角反的感兴趣信号原始相位与解缠相位

    Figure  14.  Raw phases and unwrapped phases of signals of interests from two corner reflectors under Frame #2

    图  15  三帧下重构的旋转角反

    Figure  15.  Reconstructed rotating corner reflectors under three frames

    图  16  补偿后旋转角反的距离与方位剖面图

    Figure  16.  Range and azimuth profiles of the rotating corner reflector after compensation.

    图  17  旋转角反成像补偿前后的时频图

    Figure  17.  Time-frequency images of rotating corner reflectors before and after compensation

    表  1  太赫兹 ViSAR系统参数

    Table  1.   Terahertz ViSAR system parameters

    系统指标 数值
    飞机型号 Cessna 208B
    雷达载频 216 GHz
    信号带宽 900 MHz
    地距/方位分辨率 0.18 m/0.17 m
    工作模式 条带模式
    飞行速度 219.6 km/h
    飞行高度 1.34 km
    地面海拔 0.34 km
    下视角 71.8°
    脉冲重复频率 16 kHz
    合成孔径时间 0.2 s
    方位波束宽度 0.745°
    成像帧率 5 Hz
    极化方式 VV极化
    下载: 导出CSV
  • [1] CUMMING I G and WONG F H. Digital Processing of Synthetic Aperture Radar Data[M]. Boston: Artech House, 2005: 13–78.
    [2] 李超, 李悦丽, 安道祥, 等. 基于视觉注意机制的UWB SAR叶簇隐蔽目标变化检测[J]. 电子学报, 2016, 44(1): 39–45. doi: 10.3969/j.issn.0372-2112.2016.01.007.

    LI Chao, LI Yueli, AN Daoxiang, et al. UWB SAR change detection of foliage-concealed targets based on visual attention[J]. Acta Electronica Sinica, 2016, 44(1): 39–45. doi: 10.3969/j.issn.0372-2112.2016.01.007.
    [3] SONG Juyoung, KIM D J, HWANG J H, et al. Effective vessel recognition in high resolution SAR images using quantitative and qualitative training data enhancement from target velocity phase refocusing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 5201714. doi: 10.1109/TGRS.2023.3346171.
    [4] ZHU Xiaoxiang and BAMLER R. Very high resolution spaceborne SAR tomography in urban environment[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(12): 4296–4308. doi: 10.1109/TGRS.2010.2050487.
    [5] 邓彬, 吴称光, 秦玉亮, 等. 合成孔径雷达微动目标指示(SAR/MMTI)研究进展[J]. 电子学报, 2013, 41(12): 2436–2442. doi: 10.3969/j.issn.0372-2112.2013.12.018.

    DENG Bin, WU Chengguang, QIN Yuliang, et al. Advances in synthetic aperture radar micro-motion target indication (SAR/MMTI)[J]. Acta Electronica Sinica, 2013, 41(12): 2436–2442. doi: 10.3969/j.issn.0372-2112.2013.12.018.
    [6] WANG Qi, PEPIN M, WRIGHT A, et al. Reduction of vibration-induced artifacts in synthetic aperture radar imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(6): 3063–3073. doi: 10.1109/TGRS.2013.2269138.
    [7] FAN Lei, WANG Hongqiang, YANG Qi, et al. THz-ViSAR-Oriented fast indication and imaging of rotating targets based on nonparametric method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 5217515. doi: 10.1109/TGRS.2024.3427653.
    [8] 陈思伟, 崔兴超, 李铭典, 等. 基于深度CNN模型的SAR图像有源干扰类型识别方法[J]. 雷达学报, 2022, 11(5): 897–908. doi: 10.12000/JR22143.

    CHEN Siwei, CUI Xingchao, LI Mingdian, et al. SAR image active jamming type recognition based on deep CNN model[J]. Journal of Radars, 2022, 11(5): 897–908. doi: 10.12000/JR22143.
    [9] 孙光才, 白雪茹, 周峰, 等. 一种新的无源压制性SAR干扰方法[J]. 电子与信息学报, 2009, 31(3): 610–613. doi: 10.3724/SP.J.1146.2007.01885.

    SUN Guangcai, BAI Xueru, ZHOU Feng, et al. A new passive barrage jamming method for SAR[J]. Journal of Electronics & Information Technology, 2009, 31(3): 610–613. doi: 10.3724/SP.J.1146.2007.01885.
    [10] 全斯农, 范晖, 代大海, 等. 一种基于精细极化目标分解的舰船箔条云识别方法[J]. 雷达学报, 2021, 10(1): 61–73. doi: 10.12000/JR20123.

    QUAN Sinong, FAN Hui, DAI Dahai, et al. Recognition of ships and chaff clouds based on sophisticated polarimetric target decomposition[J]. Journal of Radars, 2021, 10(1): 61–73. doi: 10.12000/JR20123.
    [11] 吴国庆, 王罗胜斌, 庞晨, 等. 雷达极化域变焦角反组合体对抗方法: 抗冲淡式干扰[J]. 电子学报, 2022, 50(12): 2969–2983. doi: 10.12263/DZXB.20220979.

    WU Guoqing, WANG Luoshengbin, PANG Chen, et al. Radar polarization modulation countermeasures for combined corner reflector: Anti diluted jamming[J]. Acta Electronica Sinica, 2022, 50(12): 2969–2983. doi: 10.12263/DZXB.20220979.
    [12] 李玉鹏, 王吉军, 苏荣华, 等. 吸收散射型伪装遮障遮蔽性能仿真分析[J]. 防护工程, 2021, 43(2): 68–72. doi: 10.3969/j.issn.1674-1854.2021.02.010.

    LI Yupeng, WANG Jijun, SU Ronghua, et al. Simulation analysis of the shielding performance of absorption-scattering camouflage barrier[J]. Protective Engineering, 2021, 43(2): 68–72. doi: 10.3969/j.issn.1674-1854.2021.02.010.
    [13] LI Xiang, DENG Bin, QIN Yuliang, et al. The influence of target micromotion on SAR and GMTI[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(7): 2738–2751. doi: 10.1109/TGRS.2011.2104965.
    [14] 王雪松. 雷达极化技术研究现状与展望[J]. 雷达学报, 2016, 5(2): 119–131. doi: 10.12000/JR16039.

    WANG Xuesong. Status and prospects of radar polarimetry techniques[J]. Journal of Radars, 2016, 5(2): 119–131. doi: 10.12000/JR16039.
    [15] FAN Lei, WANG Hongqiang, YANG Qi, et al. High-Quality airborne terahertz video SAR imaging based on echo-driven robust motion compensation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 2001817. doi: 10.1109/TGRS.2024.3357697.
    [16] LI Yuliang, LIU Jialu, LI Jin, et al. An extend Kaiser distribution optimization phase compensation algorithm for terahertz airborne SAR imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 5215815. doi: 10.1109/TGRS.2024.3420788.
    [17] ZHANG Ye, WANG Hongqiang, ZENG Yang, et al. Three-dimensional surface reconstruction of space targets using a terahertz MIMO linear array based on multilayer wideband frequency interferometry techniques[J]. IEEE Transactions on Terahertz Science and Technology, 2021, 11(4): 353–366. doi: 10.1109/TTHZ.2021.3067171.
    [18] LI Yuliang, MIN Rui, LI Jin, et al. Terahertz circular SAR imaging algorithm based on the extraction of scattering characteristics of target structures[J]. IEEE Geoscience and Remote Sensing Letters, 2024, 21: 3504905. doi: 10.1109/LGRS.2024.3379171.
    [19] FAN Lei, WANG Hongqiang, YANG Qi, et al. High frame-rate and low-latency video SAR based on robust Doppler parameters estimation in the terahertz regime[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5207016. doi: 10.1109/TGRS.2023.3271310.
    [20] 吴涵, 吴福伟, 尚士泽, 等. 太赫兹视频SAR多普勒中心估计方法[J]. 太赫兹科学与电子信息学报, 2022, 20(11): 1123–1129. doi: 10.11805/TKYDA2021295.

    WU Han, WU Fuwei, SHANG Shize, et al. Doppler centroid frequency estimation method based on THz video-SAR[J]. Journal of Terahertz Science and Electronic Information Technology, 2022, 20(11): 1123–1129. doi: 10.11805/TKYDA2021295.
    [21] DAMINI A, BALAJI B, PARRY C, et al. A videoSAR mode for the x-band wideband experimental airborne radar[C]. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, Orlando, USA, 2010: 76990E. doi: 10.1117/12.855376.
    [22] WELLS L, SORENSEN K, DOERRY A, et al. Developments in SAR and IFSAR systems and technologies at sandia national laboratories[C]. 2003 IEEE Aerospace Conference Proceedings, Big Sky, USA, 2003: 1085–1095. doi: 10.1109/AERO.2003.1235522.
    [23] FRIOUD M, WAHLEN A, WELLIG P, et al. Processing of MIRANDA35 FMCW-SAR data using a time-domain algorithm[C]. 10th European Conference on Synthetic Aperture Radar, Berlin, Germany, 2014: 1–4.
    [24] PALM S, SOMMER R, JANSSEN D, et al. Airborne circular W-Band SAR for multiple aspect urban site monitoring[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(9): 6996–7016. doi: 10.1109/TGRS.2019.2909949.
    [25] KIM S H, FAN R, and DOMINSKI F. ViSAR: A 235 GHz radar for airborne applications[C]. 2018 IEEE Radar Conference, Oklahoma, USA, 2018: 1549–1554. doi: 10.1109/RADAR.2018.8378797.
    [26] 王宏强, 邓彬, 秦玉亮. 太赫兹雷达技术[J]. 雷达学报, 2018, 1(7): 1–21. doi: 10.12000/JR17107.

    WANG Hongqiang, DENG Bin, and QIN Yuliang. Review of terahertz radar technology[J]. Journal of Radars, 2018, 7(1): 1–21. doi: 10.12000/JR17107.
    [27] XING Mengdao, JIANG Xiuwei, WU Renbiao, et al. Motion compensation for UAV SAR based on raw radar data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(8): 2870–2883. doi: 10.1109/TGRS.2009.2015657.
    [28] GAO Jingkun, QIN Yuliang, DENG Bin, et al. Terahertz wide-angle imaging and analysis on plane-wave criteria based on inverse synthetic aperture techniques[J]. Journal of Infrared, Millimeter, and Terahertz Waves, 2016, 37(4): 373–393. doi: 10.1007/s10762-016-0249-x.
    [29] 丁金闪, 仲超, 温利武, 等. 视频合成孔径雷达双域联合运动目标检测方法[J]. 雷达学报, 2022, 11(3): 313–323. doi: 10.12000/JR22036.

    DING Jinshan, ZHONG Chao, WEN Liwu, et al. Joint detection of moving target in video synthetic aperture radar[J]. Journal of Radars, 2022, 11(3): 313–323. doi: 10.12000/JR22036.
    [30] KHOSRAVI M R and SAMADI S. Mobile multimedia computing in cyber-physical surveillance services through UAV-borne Video-SAR: A taxonomy of intelligent data processing for IoMT-enabled radar sensor networks[J]. Tsinghua Science and Technology, 2022, 27(2): 288–302. doi: 10.26599/TST.2021.9010013.
    [31] 赵雨露, 张群英, 李超, 等. 视频合成孔径雷达振动误差分析及补偿方案研究[J]. 雷达学报, 2015, 4(2): 230–239. doi: 10.12000/JR14153.

    ZHAO Yulu, ZHANG Qunying, LI Chao, et al. Vibration error analysis and motion compensation of video synthetic aperture radar[J]. Journal of Radars, 2015, 4(2): 230–239. doi: 10.12000/JR14153.
    [32] 李亚超, 王家东, 张廷豪, 等. 弹载雷达成像技术发展现状与趋势[J]. 雷达学报, 2022, 11(6): 943–973. doi: 10.12000/JR22119.

    LI Yachao, WANG Jiadong, ZHANG Tinghao, et al. Present situation and prospect of missile-borne radar imaging technology[J]. Journal of Radars, 2022, 11(6): 943–973. doi: 10.12000/JR22119.
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  • 收稿日期:  2024-08-31
  • 修回日期:  2024-10-15

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