高时相星载序贯SAR图像运动目标检测方法

陈杰 杨威 王亚敏 李春升

陈杰, 杨威, 王亚敏, 等. 高时相星载序贯SAR图像运动目标检测方法[J]. 雷达学报, 2022, 11(6): 1048–1060. doi: 10.12000/JR22184
引用本文: 陈杰, 杨威, 王亚敏, 等. 高时相星载序贯SAR图像运动目标检测方法[J]. 雷达学报, 2022, 11(6): 1048–1060. doi: 10.12000/JR22184
CHEN Jie, YANG Wei, WANG Yamin, et al. Moving target monitoring algorithm based on high-frame-rate SAR images[J]. Journal of Radars, 2022, 11(6): 1048–1060. doi: 10.12000/JR22184
Citation: CHEN Jie, YANG Wei, WANG Yamin, et al. Moving target monitoring algorithm based on high-frame-rate SAR images[J]. Journal of Radars, 2022, 11(6): 1048–1060. doi: 10.12000/JR22184

高时相星载序贯SAR图像运动目标检测方法

doi: 10.12000/JR22184
基金项目: 国家自然科学基金(62271028)
详细信息
    作者简介:

    陈 杰,博士,教授,主要研究方向为高分辨率宽覆盖星载SAR成像探测机理、超高分辨率星载 SAR成像理论与方法、星载SAR电离层效应精细补偿等

    杨 威,博士,副教授,主要研究方向为星载 SAR高分辨率雷达信号仿真与成像技术、新体制雷达技术

    王亚敏,博士,博士后,主要研究方向为星载 SAR成像处理、运动目标检测和视频SAR处理等

    李春升,教授,博士生导师,主要研究方向为星载 SAR系统总体与仿真、多源遥感图像信息融合、信息获取与处理等

    通讯作者:

    杨威 09707@buaa.edu.cn

  • 责任主编:孙显 Corresponding Editor: SUN Xian
  • 中图分类号: TN957

Moving Target Monitoring Algorithm Based on High-frame-rate SAR Images

Funds: The National Natural Science Foundation of China (62271028)
More Information
  • 摘要: 该文针对低信杂噪比条件下运动目标检测难的现状,提出了高时相星载序贯合成孔径雷达(SAR)图像运动目标检测方法。首先,根据检测机理的不同将现有星载SAR运动目标检测方法分为3类,并进行了对比分析;其次,基于凝视观测模式建模分析了高帧频序贯SAR图像获取方式;在此基础上,将动目标检测等效为未知尺度、未知到达时间的一维瞬态微弱扰动信号检测,并理论分析了沿时间维高帧频序贯SAR图像间动目标幅度扰动的sinc函数形式,背景杂波幅度的缓变和系统噪声幅度的无规则快变状态;再次,为实现目标和杂波、噪声的可分性,基于核函数机理实现了动目标在高维空间的深度关联;最后,通过仿真和真实数据验证了所提方法的有效性,并分析了检测性能。性能分析结果表明在低信杂噪比条件下所提方法检测性能优于传统的恒虚警类方法。

     

  • 图  1  高时相星载SAR回波仿真流程图

    Figure  1.  The flowchart of high-frame-rate spaceborne SAR simulation

    图  2  高时相星载SAR图像序列获取

    Figure  2.  The process of high-frame-rate spaceborne SAR images

    图  3  沿时序目标一维瞬态扰动示意图

    Figure  3.  The schematic diagram of one-dimensional temporary disturbance of moving target along time series

    图  4  30 m分辨率时运动目标方位向散焦情况

    Figure  4.  The defocus of moving target with 30 m resolution along azimuth direction

    图  5  动目标、杂波和噪声幅度沿时序变化示意图

    Figure  5.  The amplitude variation of moving target, clutter and noise along time series

    图  6  基于核函数的信号高维映射流程图

    Figure  6.  The flowchart of high-dimensional mapping based on kernel function

    图  7  运动目标、杂波和噪声信号高维映射结果

    Figure  7.  The high-dimensional mapping results of moving target, clutter and noise

    图  8  基于高时相SAR的动目标检测流程图

    Figure  8.  The flowchart of moving target detection based on high-frame-rate SAR images

    图  9  不同SCNR下慢速目标检测结果

    Figure  9.  Detection results of slow moving targets with different SCNR

    图  10  不同SCNR下快速目标检测结果

    Figure  10.  Detection results of fast moving targets with different SCNR

    图  11  TerraSAR-X数据验证结果

    Figure  11.  Verification results of TerraSAR-X data

    图  12  真实逆SAR数据验证结果

    Figure  12.  Verification results of real inverse SAR results

    图  13  运动目标检测性能随窗口长度的变化

    Figure  13.  Detection performance of moving targets with different signal length

    图  14  相同条件下检测性能对比

    Figure  14.  The comparison of detection performance based on different methods

    表  1  雷达系统仿真参数

    Table  1.   The simulation parameters of radar system

    参数数值
    中心视角(°)35.0
    轨道高度(km)1000.0
    波长(m)0.03125
    天线长度(m)4.0
    天线高度(m)1.8
    轨道倾角(°)97.44
    脉冲重复频率(Hz)4200
    系统带宽(MHz)420
    采样率(MHz)500
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出版历程
  • 收稿日期:  2022-09-08
  • 修回日期:  2022-11-17
  • 网络出版日期:  2022-11-28
  • 刊出日期:  2022-12-28

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