空间目标在轨状态雷达成像估计技术综述

周叶剑 马岩 张磊 钟卫军

周叶剑, 马岩, 张磊, 等. 空间目标在轨状态雷达成像估计技术综述[J]. 雷达学报, 2021, 10(4): 607–621. doi: 10.12000/JR21086
引用本文: 周叶剑, 马岩, 张磊, 等. 空间目标在轨状态雷达成像估计技术综述[J]. 雷达学报, 2021, 10(4): 607–621. doi: 10.12000/JR21086
ZHOU Yejian, MA Yan, ZHANG Lei, et al. Review of on-orbit state estimation of space targets with radar imagery[J]. Journal of Radars, 2021, 10(4): 607–621. doi: 10.12000/JR21086
Citation: ZHOU Yejian, MA Yan, ZHANG Lei, et al. Review of on-orbit state estimation of space targets with radar imagery[J]. Journal of Radars, 2021, 10(4): 607–621. doi: 10.12000/JR21086

空间目标在轨状态雷达成像估计技术综述

doi: 10.12000/JR21086
基金项目: 国家自然科学基金(61771372)
详细信息
    作者简介:

    周叶剑(1993–),男,浙江台州人,博士,浙江工业大学信息工程学院特聘副研究员,硕士生导师。主要研究方向为SAR/ISAR成像与图像解译、多源信息融合

    马 岩(1977–),男,山东菏泽人,硕士,北京跟踪与通信技术研究所副研究员。研究方向为光电信息处理与分析、目标特性与识别

    张 磊(1984–),男,浙江金华人,博士,现为中山大学电子与通信学院教授,博士生导师。研究方向为雷达信号处理、SAR/ISAR成像与目标识别

    钟卫军(1982–),男,浙江衢州人,博士,现为西安卫星测量中心高级工程师。研究方向为太空态势感知信息处理、目标特性与识别

    通讯作者:

    马岩 mayan888@sina.com

    张磊 zhanglei57@mail.sysu.edu.cn

  • 责任主编:许小剑 Corresponding Editor: XU Xiaojian
  • 中图分类号: TN975

Review of On-orbit State Estimation of Space Targets with Radar Imagery(in English)

Funds: The National Natural Science Foundation of China (61771372)
More Information
  • 摘要: 空间目标状态估计旨在获取目标在轨姿态运动和几何结构等状态参数,是完成目标动作意图分析、排查潜在故障威胁和预判在轨态势等任务的关键技术。通过雷达光电成像信息处理实现在轨姿态估计是空间目标状态分析的重要途径,当前已经形成了一系列代表性实用方法。该文首先简要介绍了国内外用于空间目标监测的地基逆合成孔径雷达发展现状;重点针对空间目标时序特征匹配、三维成像重建和多视融合姿态估计多类代表性方法进行原理介绍与技术总结:数据特征匹配的状态估计性能可靠但依赖目标模型先验;三维几何重建的状态估计具备目标精细刻画潜力但观测几何要求高。同时,该文也对空间目标在轨状态估计方向未来发展趋势进行了展望。

     

  • 图  1  TIRA空间目标成像观测结果[13-15]

    Figure  1.  ISAR imaging result of three space targets by TIRA system[13-15]

    图  2  Envisat与其搭载的RRA结构模型(@ESA)

    Figure  2.  Envisat and its RRA courtesy of ESA

    图  3  2013年7月Graz站点Envisat卫星CCR相对位置变化测量结果[17]

    Figure  3.  Range residuals calculated for Envisat pass measured by Graz SLR station on July, 2013[17]

    图  4  2013年Envisat自旋周期变化趋势分析[17](黑点为目标真实自旋周期;灰点为Graz站观测得到的CCR自旋周期)

    Figure  4.  Spin period analysis of Envisat during year 2013[17] (black points Inertial spin period) and (gray points apparent spin period)

    图  5  空间目标地基雷达RCS测量观测几何

    Figure  5.  RCS measuring geometry configuration of space targets via ground-based radar

    图  6  实测RCS序列与角度优化后RCS模板仿真结果对比[21]

    Figure  6.  Comparison between the measured RCS sequences and the RCS sequences[21]

    图  7  文献[23]中的目标姿态估计流程

    Figure  7.  The flowchart of attitude estimation method in Ref. [23]

    图  8  MOWA目标姿态拟合软件处理界面[27]

    Figure  8.  Graphical interface of MOWA target attitude fitting[27]

    图  9  空间约束下的Envisat序列姿态关联估计[28]

    Figure  9.  Attitude estimation for Envisat sequence frames after constraining the search space[28]

    图  10  目标散射点雷达一维距离序列录取示意图[35]

    Figure  10.  Recording the distance sequence of target scattering points through radar ranging[35]

    图  11  舰船目标散射点三维重建结果[37]

    Figure  11.  The scattering points reconstruction result of the ship[37]

    图  12  稀疏观测条件下航天飞机三维重建结果[38]

    Figure  12.  The reconstruction result of shuttle in sparse observation[38]

    图  13  美国MIT林肯实验室空间目标InISAR测量系统[45]

    Figure  13.  The InISAR measuring system for space targets in MIT Lab[45]

    图  14  SPASE卫星三维干涉过程[46]

    Figure  14.  The InISAR processing of SPASE satellite[46]

    图  15  Yake-42干涉ISAR三维成像结果[49]

    Figure  15.  The InISAR 3D imaging result of Yake-42[49]

    图  16  ISAR投影成像模型

    Figure  16.  The geometrical model of ISAR projection imaging

    图  17  原始观测序列与估计重建图像序列对比[51]

    Figure  17.  The comparison between the original observation sequence and the reproduced sequence with estimated attitude parameters[51]

    图  18  KPEN关键点提取流程[53]

    Figure  18.  Target scattering point extraction using KPEN[53]

    图  19  多站ISAR同步成像瞬时姿态测量[54]

    Figure  19.  Target instantaneous attitude estimation via multiple-station ISAR imaging[54]

    图  20  同视角光电成像瞬时姿态测量[55]

    Figure  20.  Target instantaneous attitude estimation via optical-and-radar joint imaging[55]

    图  21  文献[66]中的目标姿态估计流程

    Figure  21.  The flowchart of attitude estimation method in Ref. [66]

    图  1  ISAR imaging result of three space targets by the TIRA system[13-15]

    图  2  Envisat and its RRA courtesy of ESA

    图  3  Range residuals calculated for Envisat pass measured by Graz SLR station on July 12, 2013[17]

    图  4  Spin period analysis of Envisat in 2013[17] (black points indicate an inertial spin period and gray points apparent spin period)

    图  5  RCS measuring geometry configuration of space targets via ground-based radar

    图  6  Comparison between measured RCS sequences and the RCS sequences[21]

    图  7  The flowchart of attitude estimation method in Ref. [23]

    图  8  Graphical interface of MOWA target attitude fitting[27]

    图  9  Attitude estimation for Envisat sequence frames after constraining the search space[28]

    图  10  Recording the distance sequence of target scattering points through radar ranging[35]

    图  11  Scattering point reconstruction result of the ship[37]

    图  12  Reconstruction result of shuttle in sparse observation[38]

    图  13  InISAR measuring system for space targets in MIT Lab[45]

    图  14  InISAR processing of SPASE satellite[46]

    图  15  InISAR 3D imaging result of Yake-42[49]

    图  16  Geometrical model of ISAR projection imaging

    图  17  Comparison between the original observation sequence and the reproduced sequence with estimated attitude parameters[51]

    图  18  Target scattering point extraction using KPEN[53]

    图  19  Target instantaneous attitude estimation via multiple-station ISAR imaging[54]

    图  20  Target instantaneous attitude estimation via optical-radar joint imaging[55]

    图  21  Flowchart of the attitude estimation method in Ref. [66]

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出版历程
  • 收稿日期:  2021-06-28
  • 修回日期:  2021-07-30
  • 网络出版日期:  2021-08-23

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