基于稀疏匹配滤波的TomoSAR三维成像

刘慧 赵春萌 陈鹏飞 王彦植 屈明昊 肖宁

刘慧, 赵春萌, 陈鹏飞, 等. 基于稀疏匹配滤波的TomoSAR三维成像[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR25038
引用本文: 刘慧, 赵春萌, 陈鹏飞, 等. 基于稀疏匹配滤波的TomoSAR三维成像[J]. 雷达学报(中英文), 待出版. doi: 10.12000/JR25038
LIU Hui, ZHAO Chunmeng, CHEN Pengfei, et al. Sparse matching filtering algorithm for tomographic SAR imaging[J]. Journal of Radars, in press. doi: 10.12000/JR25038
Citation: LIU Hui, ZHAO Chunmeng, CHEN Pengfei, et al. Sparse matching filtering algorithm for tomographic SAR imaging[J]. Journal of Radars, in press. doi: 10.12000/JR25038

基于稀疏匹配滤波的TomoSAR三维成像

DOI: 10.12000/JR25038 CSTR: 32380.14.JR25038
基金项目: 国家自然科学基金(61501019),中国高校产学研创新基金(2022IT229)
详细信息
    作者简介:

    刘 慧,副教授,硕士生导师,主要研究方向为SAR成像、InSAR、TomoSAR、雷达信号处理等

    赵春萌,硕士生,主要研究方向为TomoSAR成像、SAR三维解模糊等

    陈鹏飞,硕士生,主要研究方向为星载SAR三维成像

    王彦植,硕士生,主要研究方向为D-TomoSAR成像

    屈明昊,硕士生,主要研究方向为多模态多维信号处理

    肖 宁,讲师,主要研究方向为信号处理、计算视觉等

    通讯作者:

    刘慧 liuhui@bucea.edu.cn

  • 责任主编:毕辉 Corresponding Editor: BI Hui
  • 中图分类号: TN957.5

Sparse Matching Filtering Algorithm for Tomographic SAR Imaging

Funds: The National Natural Science Foundation of China (61501019), China Higher Education Institution Industry-University-Research Innovation Fund (2022IT229)
More Information
  • 摘要: 层析SAR(TomoSAR)成像技术已经成为获取三维SAR点云的关键技术。然而,如果忽略斜距垂向的二次相位,可能会导致目标在高程方向的散焦问题,这是由于层析SAR成像中第三维也可能存在菲涅耳衍射所导致的。该文利用光学成像中的衍射原理解释了SAR成像中的衍射问题同样在第三维存在,并提出采用稀疏匹配滤波方法对第三维进行聚焦。第三维稀疏匹配滤波的关键在于构建稀疏相位补偿因子,进而构建稀疏匹配滤波器。首先根据TomoSAR影像的空间几何基线,构建第三维归一化的稀疏频率;然后,结合波长、距离、孔径等参数,根据菲涅耳积分特性构建频域稀疏匹配滤波器;最后,使用频域稀疏滤波器对稀疏采样的SAR图像进行相位补偿,再利用经典的稀疏成像算法(如压缩感知、似然比检测方法等)进行高程即第三维目标检测。该文采用中国科学院空天信息创新研究院的机载SAR数据,运用该文构建的频域稀疏匹配滤波器对其进行实验,实验结果验证了该文所提的方法能够解决层析SAR在菲涅耳衍射情况下导致的散焦问题,从而改善散焦引起的目标位置和后向散射信息不准确的问题。

     

  • 图  1  TomoSAR系统的几何模型

    Figure  1.  Geometric model of TomoSAR system

    图  2  光的衍射几何

    Figure  2.  Diffraction geometry of light

    图  3  机载TomoSAR系统参数仿真结果

    Figure  3.  Simulation results by parameters of airborne TomoSAR system

    图  4  TerraSAR-X系统参数仿真结果

    Figure  4.  Simulation results by parameters of TerraSAR-X system

    图  5  稀疏匹配滤波三维成像流程图

    Figure  5.  Flowchart of sparse matched filtering 3D imaging

    图  6  单点目标情况下匹配滤波验证

    Figure  6.  Verification of matched filtering under the condition of single target

    图  7  两点目标情况下匹配滤波验证

    Figure  7.  Verification of matched filtering under the condition of two targets

    图  8  天津临港商务大厦

    Figure  8.  Tianjin Lingang Business Building

    图  9  不做匹配滤波时方位向为500的切片处进行TomoSAR成像结果

    Figure  9.  TomoSAR imaging results at the 500th slice in azimuth without matched filtering

    图  10  匹配滤波后方位向为500的切片处进行TomoSAR成像结果

    Figure  10.  TomoSAR imaging results at the 500th slice in azimuth with matched filtering

    图  11  不同长度基线干涉相位图

    Figure  11.  Interferograms with different baselines

    图  12  干涉相位图去噪结果

    Figure  12.  Denoised interferograms

    图  13  不同区域的模糊值

    Figure  13.  Ambiguity value indifferent regions

    图  14  方位向为500的切片处TomoSAR点云

    Figure  14.  TomoSAR point clouds at the 500th slice in azimuth with matched filtering

    图  15  观测场景TomoSAR点云

    Figure  15.  TomoSAR point clouds of the observed scene

    表  1  两组TomoSAR数据参数

    Table  1.   Two sets of TomoSAR data parameters

    参数 符号 机载数据(m) 星载数据(m)
    最小基线间隔 ${B_{\min }}$ 0.1071 20
    最大基线长度 ${B_{\max }}$ 0.442 400
    波长 $\lambda $ 0.0197 0.031
    斜距 r 482.0413 603638.971
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  • 收稿日期:  2025-02-25
  • 修回日期:  2025-08-17

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