联合距离方位二维NCS的星弹双基前视SAR成像算法

刘裕洲 蔡天倚 李亚超 宋炫 王选琪 安培赟

刘裕洲, 蔡天倚, 李亚超, 等. 联合距离方位二维NCS的星弹双基前视SAR成像算法[J]. 雷达学报, 2023, 12(6): 1202–1214. doi: 10.12000/JR23144
引用本文: 刘裕洲, 蔡天倚, 李亚超, 等. 联合距离方位二维NCS的星弹双基前视SAR成像算法[J]. 雷达学报, 2023, 12(6): 1202–1214. doi: 10.12000/JR23144
LIU Yuzhou, CAI Tianyi, LI Yachao, et al. A range and azimuth combined two-dimensional NCS algorithm for spaceborne-missile bistatic forward-looking SAR[J]. Journal of Radars, 2023, 12(6): 1202–1214. doi: 10.12000/JR23144
Citation: LIU Yuzhou, CAI Tianyi, LI Yachao, et al. A range and azimuth combined two-dimensional NCS algorithm for spaceborne-missile bistatic forward-looking SAR[J]. Journal of Radars, 2023, 12(6): 1202–1214. doi: 10.12000/JR23144

联合距离方位二维NCS的星弹双基前视SAR成像算法

DOI: 10.12000/JR23144
基金项目: 国家重点研发计划(2018YFB2202500),国家自然科学基金(62171337, 62101396),陕西省重点研发计划(2017KW-ZD-12),陕西省杰出青年基金(S2020-JC-JQ-0056),中央高校基本科研基金(XJS212205),西安电子科技大学研究生创新基金(YJSJ23016)
详细信息
    作者简介:

    刘裕洲,博士生,研究方向为双基地合成孔径雷达(BiSAR)前视成像和地面动目标成像(GMTI)技术

    蔡天倚,硕士,研究方向为软件工程、雷达信号处理等

    李亚超,教授,博士生导师,研究方向为合成孔径雷达(SAR)/逆SAR (ISAR)成像、弹载SAR成像、地面运动目标检测(GMTI)、SAR图像的匹配和定向、基于现场可编程门阵列(FPGA)和数字信号处理(DSP)技术的实时信号处理以及分布式雷达

    宋 炫,博士,研究方向为双基地合成孔径雷达(SAR)前视成像技术

    王选琪,博士生,研究方向为双基地合成孔径雷达前视成像与协同探测技术

    安培赟,硕士生,研究方向为双基地合成孔径雷达前视成像与运动补偿技术

    通讯作者:

    李亚超 ycli@mail.xidian.edu.cn

  • 责任主编:李悦丽 Corresponding Editor:  LI Yueli
  • 中图分类号: TN957.52

A Range and Azimuth Combined Two-dimensional NCS Algorithm for Spaceborne-missile Bistatic Forward-looking SAR

Funds: The National Key R&D Program of China (2018YFB2202500), The National Natural Science Foundation of China (62171337, 62101396), The Key R&D program of Shaanxi Province (2017KW-ZD-12), The Shaanxi Province Funds for Distinguished Young Youths (S2020-JC-JQ-0056), The Fundamental Research Funds for the Central Universities (XJS212205), The Innovation Fund of Xidian University (YJSJ23016)
More Information
  • 摘要: 星弹双基前视SAR能够全天时全天候获取导弹前方区域高分辨图像,是一种极具潜力的成像制导技术。然而,距离和方位参数的耦合与空变,阻碍着星弹双基前视SAR向高分辨成像发展。该文首先基于低轨星载照射源与高速前视的弹载接收平台构型,推导了回波信号的精确距离多普勒域解析式。然后,在距离向上,提出距离非线性变标(NCS)算法来均衡距离徙动和距离调频率,并在二维频域一致补偿;在方位向上,该文所提算法将收发机的方位调频率进行分解,利用方位NCS消除方位调频率在方位向上的高阶空变。最后,进行二维匹配滤波,得到全局聚焦良好的SAR图像。点目标和场景仿真验证了所提算法的有效性。

     

  • 图  1  星弹双基前视SAR几何构型

    Figure  1.  Geometry configuration of spaceborne-missile bistatic forward-looking SAR

    图  2  所提距离模型误差

    Figure  2.  The error of proposed range history model

    图  3  距离预处理效果对比

    Figure  3.  Comparison of range preprocessing effect

    图  4  NCS原理示意图

    Figure  4.  Principle diagram of NCS

    图  5  所提成像算法流程图

    Figure  5.  Flowchart of the proposed imaging algorithm

    图  6  仿真点目标分布

    Figure  6.  Distribution of simulation point targets

    图  7  距离预处理前后信号的二维频谱对比

    Figure  7.  Comparison of the signal in two-dimensional spectrum before and after range preprocessing

    图  8  所提算法的点仿真成像结果

    Figure  8.  The point simulation imaging results of the proposed algorithm

    图  9  不同算法的P1点二维等高线图

    Figure  9.  Two-dimensional contour maps of the point P1 using different algorithms

    图  10  不同算法的P1点方位剖面图

    Figure  10.  Azimuth profile of the point P1 using different algorithms

    图  11  不同算法的P1点距离剖面图

    Figure  11.  Range profile of the point P1 using different algorithms

    图  12  不同算法的P2点二维等高线图

    Figure  12.  Two-dimensional contour maps of the point P2 using different algorithms

    图  13  不同算法的P2点方位剖面图

    Figure  13.  Azimuth profile of the point P2 using different algorithms

    图  14  不同算法的P2点距离剖面图

    Figure  14.  Range profile of the point P2 using different algorithms

    图  15  所提算法的场景仿真成像结果

    Figure  15.  Scene simulation imaging results of the proposed algorithm

    图  16  不同算法的场景成像结果放大

    Figure  16.  The amplified scene imaging results of different algorithms

    图  17  不同算法的场景仿真孤立点分析

    Figure  17.  Isolated point analysis in scene simulation of different algorithms

    表  1  雷达系统仿真参数

    Table  1.   Simulation parameters of radar system

    参数 数值
    载波波长(m) 0.05
    系统带宽(MHz) 180
    合成孔径时间(s) 3
    卫星高度(km) 755
    卫星速度(m/s) 6800
    导弹作用距离(km) 46
    导弹沿速度方向加速度(m/s2) 80
    导弹垂直速度方向加速度(m/s2) 10
    导弹速度(m/s) 1020
    场景中心点位置(km) (0,45,0)
    下载: 导出CSV

    表  2  点目标成像性能评估

    Table  2.   Point target imaging performance evaluation

    点目标 成像算法 方位向 距离向
    分辨率(m) PSLR (dB) ISLR (dB) 分辨率(m) PSLR (dB) ISLR (dB)
    ${P_1}$ TNCS算法 2.17 N/A N/A 1.63 N/A N/A
    FNCS算法 1.85 –10.54 –8.06 1.13 –11.69 –9.39
    所提算法 1.82 –13.28 –10.06 1.08 –13.27 –10.14
    ${P_2}$ TNCS算法 2.23 N/A N/A 1.78 N/A N/A
    FNCS算法 1.88 –10.47 –7.81 1.19 –10.23 –8.52
    所提算法 1.83 –13.26 –10.02 1.09 –13.26 –10.12
    下载: 导出CSV
  • [1] CHEN Hongmeng, LI Yachao, GAO Wenquan, et al. Bayesian forward-looking superresolution imaging using Doppler deconvolution in expanded beam space for high-speed platform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5105113. doi: 10.1109/TGRS.2021.3107717
    [2] 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
    [3] 林春辉. 单基/双基SAR成像若干关键问题研究[D]. [博士论文], 西安电子科技大学, 2019.

    LIN Chunhui. Study on some imaging issues of monostatic and bistatic SAR[D]. [Ph.D. dissertation], Xidian University, 2019.
    [4] NEO Y L, WONG F H, and CUMMING I G. Processing of azimuth-invariant bistatic SAR data using the range Doppler algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(1): 14–21. doi: 10.1109/TGRS.2007.909090
    [5] 刘婵. 双基地前视SAR频域成像算法研究[D]. [硕士论文], 电子科技大学, 2015.

    LIU Chan. Study on frequency-domain imaging algorithms for bistatic forward-looking SAR[D]. [Master dissertation], University of Electronic Science and Technology of China, 2015.
    [6] CHEN Si, YUAN Yue, ZHANG Shuning, et al. A new imaging algorithm for forward-looking missile-borne bistatic SAR[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(4): 1543–1552. doi: 10.1109/JSTARS.2015.2507260
    [7] ZHANG Qianghui, WU Junjie, SONG Yue, et al. Bistatic-range-Doppler-aperture wavenumber algorithm for forward-looking spotlight SAR with stationary transmitter and maneuvering receiver[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(3): 2080–2094. doi: 10.1109/TGRS.2020.3004726
    [8] PU Wei, LI Wenchao, LV Youxin, et al. An extended omega-K algorithm with integrated motion compensation for bistatic forward-looking SAR[C]. 2015 IEEE Radar Conference, Arlington, USA, 2015: 1291–1295.
    [9] FENG Dong, AN Daoxiang, and HUANG Xiaotao. An extended fast factorized back projection algorithm for missile-borne bistatic forward-looking SAR imaging[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(6): 2724–2734. doi: 10.1109/TAES.2018.2828238
    [10] LI Yachao, XU Gaotian, ZHOU Song, et al. A novel CFFBP algorithm with noninterpolation image merging for bistatic forward-looking SAR focusing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1–16. doi: 10.1109/TGRS.2022.3162230
    [11] DESAI M D and JENKINS W K. Convolution backprojection image reconstruction for spotlight mode synthetic aperture radar[J]. IEEE Transactions on Image Processing, 1992, 1(4): 505–517. doi: 10.1109/83.199920
    [12] XU Gaotian, ZHOU Song, YANG Lei, et al. Efficient fast time-domain processing framework for airborne bistatic SAR continuous imaging integrated with data-driven motion compensation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5208915. doi: 10.1109/TGRS.2021.3099204
    [13] AN Hongyang, WU Junjie, HE Zhiwei, et al. Geosynchronous spaceborne-airborne multichannel bistatic SAR imaging using weighted fast factorized backprojection method[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(10): 1590–1594. doi: 10.1109/LGRS.2019.2902036
    [14] 蒲巍. 机载双基地前视SAR运动补偿方法研究[D]. [博士论文], 电子科技大学, 2018.

    PU Wei. Research on airborne bistatic forward-looking SAR motion compensation[D]. [Ph.D. dissertation], University of Electronic Science and Technology of China, 2018.
    [15] QIU Xiaolan, HU Donghui, and DING Chibiao. Some reflections on bistatic SAR of forward-looking configuration[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(4): 735–739. doi: 10.1109/LGRS.2008.2004506
    [16] WU Junjie, YANG Jianyu, HUANG Yulin, et al. A frequency-domain imaging algorithm for translational invariant bistatic forward-looking SAR[J]. IEICE Transactions on Communications, 2013, E96.B(2): 605–612. doi: 10.1587/transcom.E96.B.605
    [17] WU Junjie, YANG Jianyu, HUANG Yulin, et al. Focusing bistatic forward-looking SAR using Chirp Scaling algorithm[C]. 2011 IEEE RadarCon, Kansas City, USA, 2011: 1036–1039. doi: 10.1109/RADAR.2011.5960693.
    [18] QI C D, SHI X M, BIAN M M, et al. Focusing forward-looking bistatic SAR data with chirp scaling[J]. Electronics Letters, 2014, 50(3): 206–207. doi: 10.1049/el.2013.3978
    [19] WU Junjie, PU Wei, HUANG Yulin, et al. Bistatic forward-looking SAR focusing using ω-k based on spectrum modeling and optimization[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(11): 4500–4512.
    [20] ZHANG Xiaohu, GU Hong, and SU Weimin. Focusing bistatic forward-looking SAR images use omega-k algorithm based on modified hyperbolic approximating[C]. 2019 International Conference on Control, Automation and Information Sciences, Chengdu, China, 2019: 1–5. doi: 10.1109/ICCAIS46528.2019.9074596.
    [21] 张强辉. 高速机动平台双基前视SAR成像方法研究[D]. [博士论文], 电子科技大学, 2019.

    ZHANG Qianghui. Imaging method research for bistatic forward-looking SAR mounted on high-speed maneuvering platform[D]. [Ph.D. dissertation], University of Electronic Science and Technology of China, 2019.
    [22] LI Yachao, ZHANG Tinghao, MEI Haiwen, et al. Focusing translational-variant bistatic forward-looking SAR data using the modified omega-K algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5203916. doi: 10.1109/TGRS.2021.3063780
    [23] ZENG Tao, WANG Rui, LI Feng, et al. A modified nonlinear chirp scaling algorithm for spaceborne/stationary bistatic SAR based on series reversion[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(5): 3108–3118. doi: 10.1109/TGRS.2012.2219057
    [24] SONG Xuan, LI Yachao, ZHANG Tinghao, et al. Focusing high-maneuverability bistatic forward-looking SAR using extended azimuth nonlinear chirp scaling algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5240814. doi: 10.1109/TGRS.2022.3228803
    [25] 陈溅来, 熊毅, 徐刚, 等. 基于子图像变标的非线性轨迹SAR成像及其自聚焦方法[J]. 雷达学报, 2022, 11(6): 1098–1109. doi: 10.12000/JR22171

    CHEN Jianlai, XIONG Yi, XU Gang, et al. Nonlinear trajectory synthetic aperture radar imaging and autofocus algorithm based on sub-image nonlinear chirp scaling[J].Journal of Radars, 2022, 11(6): 1098–1109. doi: 10.12000/JR22171
    [26] WONG F H, CUMMING I G, and LAM NEO Y. Focusing bistatic SAR data using the nonlinear chirp scaling algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(9): 2493–2505. doi: 10.1109/TGRS.2008.917599
    [27] QIU Xiaolan, HU Donghui, and DING Chibiao. An improved NLCS algorithm with capability analysis for one-stationary BiSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(10): 3179–3186. doi: 10.1109/TGRS.2008.921569
    [28] WU Junjie, SUN Zhichao, LI Zhongyu, et al. Focusing translational variant bistatic forward-looking SAR using keystone transform and extended nonlinear chirp scaling[J]. Remote Sensing, 2016, 8(10): 840. doi: 10.3390/rs8100840
    [29] MEI Haiwen, LI Yachao, XING Mengdao, et al. A frequency-domain imaging algorithm for translational variant bistatic forward-looking SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(3): 1502–1515. doi: 10.1109/TGRS.2019.2943743
    [30] LIANG Mu, SU Weimin, and GU Hong. Focusing high-resolution high forward-looking bistatic SAR with nonequal platform velocities based on keystone transform and modified nonlinear chirp scaling algorithm[J]. IEEE Sensors Journal, 2019, 19(3): 901–908. doi: 10.1109/JSEN.2018.2877387
    [31] DING Jiabiao, LI Yachao, LI Ming, et al. Focusing high maneuvering bistatic forward-looking SAR with stationary transmitter using extended keystone transform and modified frequency nonlinear chirp scaling[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 2476–2492. doi: 10.1109/JSTARS.2022.3153824
    [32] CUMMING I G and WONG F H. Digital Processing of Synthetic Aperture Radar Data: Algorithms and ImpleMentation[M]. Boston, MA, USA: Artech House, 2005: 225–362.

    CUMMING I G and WONG F H. Digital Processing of Synthetic Aperture Radar Data: Algorithms and ImpleMentation[M]. Boston, MA, USA: Artech House, 2005: 225–362.
    [33] 李燕平, 张振华, 邢孟道, 等. 基于级数反演和数值计算的广义双基SAR距离徙动成像算法[J]. 电子与信息学报, 2008, 30(12): 2800–2804. doi: 10.3724/SP.J.1146.2007.00810

    LI Yanping, ZHANG Zhenhua, XING Mengdao, et al. A novel range migration algorithm for general bistatic SAR imaging based on series reversion and numerical computation[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2800–2804. doi: 10.3724/SP.J.1146.2007.00810
    [34] 王谋, 韦顺军, 沈蓉, 等. 基于自学习稀疏先验的三维SAR成像方法[J]. 雷达学报, 2023, 12(1): 36–52. doi: 10.12000/JR22101

    WANG Mou, WEI Shunjun, SHEN Rong, et al. 3D SAR imaging method based on learned sparse prior[J]. Journal of Radars, 2023, 12(1): 36–52. doi: 10.12000/JR22101
    [35] CARDILLO G P. On the use of the gradient to determine bistatic SAR resolution[C]. International Symposium on Antennas and Propagation Society, Merging Technologies for the 90’s, Dallas, USA, 1990: 1032–1035.
  • 加载中
图(17) / 表(2)
计量
  • 文章访问数:  525
  • HTML全文浏览量:  217
  • PDF下载量:  164
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-08-29
  • 修回日期:  2023-11-11
  • 网络出版日期:  2023-12-11
  • 刊出日期:  2023-12-28

目录

    /

    返回文章
    返回