基于尺度变换原理的SAR波数域成像算法

韦维 朱岱寅 吴迪

韦维, 朱岱寅, 吴迪. 基于尺度变换原理的SAR波数域成像算法[J]. 雷达学报, 2020, 9(2): 354–362. doi: 10.12000/JR19112
引用本文: 韦维, 朱岱寅, 吴迪. 基于尺度变换原理的SAR波数域成像算法[J]. 雷达学报, 2020, 9(2): 354–362. doi: 10.12000/JR19112
WEI Wei, ZHU Daiyin, and WU Di. Wavenumber domain algorithm based on the principle of chirp scaling for SAR imaging[J]. Journal of Radars, 2020, 9(2): 354–362. doi: 10.12000/JR19112
Citation: WEI Wei, ZHU Daiyin, and WU Di. Wavenumber domain algorithm based on the principle of chirp scaling for SAR imaging[J]. Journal of Radars, 2020, 9(2): 354–362. doi: 10.12000/JR19112

基于尺度变换原理的SAR波数域成像算法

doi: 10.12000/JR19112
基金项目: 国家重点研发计划(2017YFB0502700),国家自然科学基金(61671240),航空科学基金(20182052013)
详细信息
    作者简介:

    韦 维(1996–),男,江苏人,硕士生。研究方向为超高分辨率合成孔径雷达成像技术。E-mail: weiw@nuaa.edu.cn

    朱岱寅(1974–),男,江苏人,教授,博士生导师。研究方向为合成孔径雷达/逆合成孔径雷达(SAR/ISAR)成像以及自聚焦算法,干涉SAR成像,SAR地面动目标指示,以及机载雷达动目标指示技术。自2018年开始担任《雷达学报》编委。E-mail: zhudy@nuaa.edu.cn

    吴 迪(1982–),男,河南人,副教授,硕士生导师。研究方向为雷达信号处理、地面动目标指示技术。E-mail: wudi82@nuaa.edu.cn

    通讯作者:

    朱岱寅 zhudy@nuaa.edu.cn

  • 责任主编:林赟 Corresponding Editor: LIN Yun
  • 中图分类号: TN957.5

Wavenumber Domain Algorithm Based on the Principle of Chirp Scaling for SAR Imaging

Funds: The National Key Research and Development Program of China (2017YFB0502700), The National Natural Science Foundation of China (61671240), The Aeronautical Science Foundation of China (20182052013)
More Information
  • 摘要: 距离徙动算法(RMA)作为一种合成孔径雷达(SAR)频域成像算法,理论上能够达到最优性能。然而,该算法采用逐像素点卷积运算实现Stolt映射,其计算效率无法满足SAR大数据量处理需求。据此,该文提出基于尺度变换原理(PCS)的RMA成像算法。首先,将SAR回波数据沿距离向进行划分,利用子带参考距离处2阶距离方位耦合项与高阶项对子带信号进行补偿;然后,转化非线性Stolt映射为线性形式;最后,利用PCS原理实现Stolt插值,以实现高效率的数据重采样。所提PCS-RMA算法仅利用快速傅里叶变换和复矢量相乘操作即可实现改进型Stolt映射,兼具良好的聚焦性能与较高的计算效率。基于多组仿真数据与X波段1.2 GHz带宽的机载SAR实测数据处理结果,验证了所提算法的有效性,同时该算法可进一步应用于弹载/星载/无人机载SAR数据的快速成像处理。

     

  • 图  1  聚束模式几何模型

    Figure  1.  Geometric model of spotlight mode

    图  2  残余相位误差

    Figure  2.  Residual phase error

    图  3  改进型Stolt插值处理流程

    Figure  3.  Processing flow of modified Stolt interpolation

    图  4  PCS-RMA算法处理流程

    Figure  4.  Processing flow of PCS-RMA

    图  5  点目标分布几何关系

    Figure  5.  Geometric relationship of point target distribution

    图  6  点目标IRF等高线

    Figure  6.  Contours of point target IRF

    图  7  点目标IRF距离向剖面

    Figure  7.  Range profiles of point target IRF

    图  8  点目标IRF方位向剖面

    Figure  8.  Azimuth profiles of point target IRF

    图  9  数据处理时间对比

    Figure  9.  Comparisons of data processing time

    图  10  RMA处理结果

    Figure  10.  Processing results of the traditional RMA

    图  11  PCS-RMA处理结果

    Figure  11.  Processing results of the proposed PCS-RMA

    表  1  点目标仿真参数

    Table  1.   Point target simulation parameters

    参数数值
    载频9.65 GHz
    信号带宽1.5 GHz
    脉冲重复频率1500 Hz
    载机速度100 m/s
    中心斜距10 km
    方位向分辨率0.1 m
    下载: 导出CSV

    表  2  点目标IRF聚焦性能参数

    Table  2.   Focusing performance parameters of point target IRF

    点目标距离向方位向
    PSLR(dB)ISLR(dB)IRW(m)PSLR(dB)ISLR(dB)IRW(m)
    A–13.3728–11.56360.0990–13.2710–11.14090.1017
    B–13.4564–11.58810.1001–13.3030–11.22750.1000
    C–13.5875–9.87720.1001–13.5265–10.75030.1033
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-12-16
  • 修回日期:  2020-02-13
  • 网络出版日期:  2020-04-01

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