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]

  • [1] New Mexico State University. How many satellites in space[EB/OL]. https://web.nmsu.edu/~tnuslein/ICT460/SPECIAL/Page3.htm, 2021.
    [2] 央视网. 美俄卫星太空相撞[EB/OL]. http://news.cctv.com/special/satellitecrash/home/index.shtml, 2018.
    [3] Orbital debris quarterly news[R]. NASA Orbital Debris Program Office, 2010, 14(3).
    [4] 邢孟道, 林浩, 陈溅来, 等. 多平台合成孔径雷达成像算法综述[J]. 雷达学报, 2019, 8(6): 732–757. doi: 10.12000/JR19102

    XING Mengdao, LIN Hao, CHEN Jianlai, et al. A review of imaging algorithms in multi-platform-borne synthetic aperture radar[J]. Journal of Radars, 2019, 8(6): 732–757. doi: 10.12000/JR19102
    [5] 马岩, 马驰, 解延浩, 等. 基于视频遥感卫星的空间目标光度测量[J]. 光子学报, 2019, 48(12): 1228002. doi: 10.3788/gzxb20194812.1228002

    MA Yan, MA Chi, XIE Yanhao, et al. Space target luminosity measurement based on video remote sensing satellites[J]. Acta Photonica Sinica, 2019, 48(12): 1228002. doi: 10.3788/gzxb20194812.1228002
    [6] 王雪松, 陈思伟. 合成孔径雷达极化成像解译识别技术的进展与展望[J]. 雷达学报, 2020, 9(2): 259–276. doi: 10.12000/JR19109

    WANG Xuesong and CHEN Siwei. Polarimetric synthetic aperture radar interpretation and recognition: Advances and perspectives[J]. Journal of Radars, 2020, 9(2): 259–276. doi: 10.12000/JR19109
    [7] 郭崇滨, 夏喜旺, 斯朝铭, 等. 分布式精密编队卫星相对位姿测量技术综述[J]. 航天控制, 2018, 36(6): 83–89. doi: 10.16804/j.cnki.issn1006-3242.2018.06.015

    GUO Chongbin, XIA Xiwang, SI Chaoming, et al. A survey of relative position and attitude measurement for formation flying satellite[J]. Aerospace Control, 2018, 36(6): 83–89. doi: 10.16804/j.cnki.issn1006-3242.2018.06.015
    [8] AVENT R K, SHELTON J D, and BROWN P. The ALCOR C-band imaging radar[J]. IEEE Antennas and Propagation Magazine, 1996, 38(3): 16–27. doi: 10.1109/74.511949
    [9] JAIN A and PATEL I. SAR/ISAR imaging of a nonuniformly rotating target[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(1): 317–320. doi: 10.1109/7.135457
    [10] BILL D. Wideband radar[J]. Lincoln Laboratory Journal, 2010, 18(2): 87–88.
    [11] CAMP W W, MAYHAN J T, and O’DONNELL R M. Wideband radar for ballistic missile defense and range-doppler imaging of satellites[J]. Lincoln Laboratory Journal, 2000, 12(2): 267–280.
    [12] MIT Lincoln Lab. The annual report summarizes lincoln laboratory[EB/OL]. https://archive.ll.mit.edu/publications/index.html, 2020.
    [13] Fraunhofer FHR Lab. Space observation radar TIRA[EB/OL]. https://www.fhr.fraunhofer.de/en/the-institute/technical-equipment/Space-observation-radar-TIRA.html, 2020.
    [14] VIRGILI B B, LEMMENS S, and KRAG H. Investigation on Envisat attitude motion[R]. Proceedings of the Deorbit Workshop, Noordwijk, The Netherlands, 2014.
    [15] Monitoring the re-entry of the Chinese space station Tiangong-1 with TIRA[EB/OL]. https://www.fhr.fraunhofer.de/en/businessunits/space/monitoring-the-re-entry-of-the-chinese-space-station-tiangong-1-with-tira.html, 2018.
    [16] VELLUTINI E, BIANCHI G, PARDINI C, et al. Monitoring the final orbital decay and the re-entry of Tiangong-1 with the Italian SST ground sensor network[J]. Journal of Space Safety Engineering, 2020, 7(4): 487–501. doi: 10.1016/j.jsse.2020.05.004
    [17] KUCHARSKI D, KIRCHNER G, KOIDL F, et al. Attitude and spin period of space debris envisat measured by satellite laser ranging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(12): 7651–7657. doi: 10.1109/TGRS.2014.2316138
    [18] KIRCHNER G, HAUSLEITNER W, and CRISTEA E. Ajisai spin parameter determination using Graz kilohertz satellite laser ranging data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(1): 201–205. doi: 10.1109/TGRS.2006.882254
    [19] GÓMEZ N O and WALKER S J I. Earth’s gravity gradient and eddy currents effects on the rotational dynamics of space debris objects: Envisat case study[J]. Advances in Space Research, 2015, 56(3): 494–508. doi: 10.1016/j.asr.2014.12.031
    [20] LIN Houyuan and ZHAO Changyin. An estimation of Envisat’s rotational state accounting for the precession of its rotational axis caused by gravity-gradient torque[J]. Advances in Space Research, 2018, 61(1): 182–188. doi: 10.1016/j.asr.2017.10.014
    [21] ZHONG Weijun, WANG Jiasong, JI Weijie, et al. The attitude estimation of three-axis stabilized satellites using hybrid particle swarm optimization combined with radar cross section precise prediction[J]. Proceedings of the Institution of Mechanical Engineers,Part G:Journal of Aerospace Engineering, 2016, 230(4): 713–725. doi: 10.1177/0954410015596178
    [22] LYU Jiangtao, ZHONG Weijun, LIU Hong, et al. Novel approach to determine spinning satellites’ attitude by RCS measurements[J]. Journal of Aerospace Engineering, 2021, 34(4): 04021023. doi: 10.1061/(ASCE)AS.1943-5525.0001253
    [23] D’AMICO S, BENN M, and JØRGENSEN J L. Pose estimation of an uncooperative spacecraft from actual space imagery[J]. International Journal of Space Science and Engineering, 2014, 2(2): 171–189. doi: 10.1504/IJSPACESE.2014.060600
    [24] SHARMA S and D’AMICO S. Reduced-dynamics pose estimation for non-cooperative spacecraft rendezvous using monocular vision[C]. 38th AAS Guidance and Control Conference, Colorado, USA, 2017.
    [25] SAIDI M N, DAOUDI K, KHENCHAF A, et al. Automatic target recognition of aircraft models based on ISAR images[C]. 2009 IEEE International Geoscience and Remote Sensing Symposium, Cape Town, South Africa, 2009: IV-685–IV-688.
    [26] LEMMENS S, KRAG H, and ROSEBROCK J. Radar mappings for attitude analysis of objects in orbit[C]. The 6th European Conference on Space Debris, Darmstadt, Germany, 2013: 20–24.
    [27] LEMMENS S and KRAG H. Sensitivity of automated attitude determination form ISAR radar mappings[C]. Advanced Maui Optical and Space Surveillance Technologies Conference(AMOS), Tokyo, Japan, 2013.
    [28] AVILÉS M, MARGARIT G, CANETRI M, et al. Automated attitude estimation from ISAR images[C]. The 7th European Conference on Space Debris, Darmstadt, Germany, 2017: 1–13.
    [29] 杨长才, 魏丽芳, 周术诚, 等. 基于单目视觉的空间非合作目标相对姿态估计方法[J]. 福建农林大学学报: 自然科学版, 2015, 44(6): 657–661. doi: 10.13323/j.cnki.j,fafunat.sci.2015.06.017

    YANG Changcai, WEI Lifang, ZHOU Shucheng, et al. Monocular vision-based relative attitude estimation for non-cooperative space targets[J]. Journal of Fujian Agriculture and Forestry University:Natural Science Edition, 2015, 44(6): 657–661. doi: 10.13323/j.cnki.j,fafunat.sci.2015.06.017
    [30] 丁赤飚, 仇晓兰, 徐丰, 等. 合成孔径雷达三维成像——从层析、阵列到微波视觉[J]. 雷达学报, 2019, 8(6): 693–709. doi: 10.12000/JR19090

    DING Chibiao, QIU Xiaolan, XU Feng, et al. Synthetic aperture radar three-dimensional imaging——from TomoSAR and array InSAR to microwave vision[J]. Journal of Radars, 2019, 8(6): 693–709. doi: 10.12000/JR19090
    [31] 金亚秋. 多模式遥感智能信息与目标识别: 微波视觉的物理智能[J]. 雷达学报, 2019, 8(6): 710–716. doi: 10.12000/JR19083

    JIN Yaqiu. Multimode remote sensing intelligent information and target recognition: Physical intelligence of microwave vision[J]. Journal of Radars, 2019, 8(6): 710–716. doi: 10.12000/JR19083
    [32] MA Y, SOATTO S, KOSECKA J, et al. An Invitation to 3-D Vision: From Images to Geometric Models[M]. Cambridge: Springer, 2012.
    [33] HARTLEY R and ZISSERMAN A. Multiple View Geometry in Computer Vision[M]. Cambridge: Cambridge University Press, 2003.
    [34] TOMASI C and TAKEO K. Shape and motion from image streams under orthography: A factorization method[J]. International Journal of Computer Vision, 1992, 9(2): 137–154. doi: 10.1007/BF00129684
    [35] FERRARA M, ARNOLD G, and STUFF M. Shape and motion reconstruction from 3D-to-1D orthographically projected data via object-image relations[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(10): 1906–1912. doi: 10.1109/TPAMI.2008.294
    [36] FERRARA M, ARNOLD G, PARKER J T, et al. Robust estimation of shape invariants[C]. 2012 IEEE Radar Conference, Atlanta, USA, 2012: 167–172.
    [37] MCFADDEN F E. Three-dimensional reconstruction from ISAR sequences[C]. Proceedings of SPIE 4744 Sensor Technology and Data Visualization, Orlando, USA, 2002: 58–67.
    [38] 王峰, 徐丰, 金亚秋. 利用序列ISAR图像获取空间目标3-D信息的方法[J]. 遥感技术与应用, 2016, 31(5): 900–906. doi: 10.11873/j.issn.1004-0323.2016.05.0900

    WANG Feng, XU Feng, and JIN Yaqiu. 3-D information reconstruction of a space target from 2-D ISAR image sequence[J]. Remote Sensing Technology and Application, 2016, 31(5): 900–906. doi: 10.11873/j.issn.1004-0323.2016.05.0900
    [39] WANG Feng, XU Feng, and JIN Yaqiu. Three-dimensional reconstruction from a multiview sequence of sparse ISAR imaging of a space target[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(2): 611–620. doi: 10.1109/TGRS.2017.2737988
    [40] LINDSAY J E. Angular glint and the moving, rotating, complex radar target[J]. IEEE Transactions on Aerospace and Electronic Systems, 1968, AES-4(2): 164–173. doi: 10.1109/TAES.1968.5408954
    [41] YIN Hongcheng and HUANG Peikang. Further comparison between two concepts of radar target angular glint[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(1): 372–380. doi: 10.1109/TAES.2008.4517012
    [42] 刘承兰, 高勋章, 黎湘. 干涉式逆合成孔径雷达成像技术综述[J]. 信号处理, 2011, 27(5): 737–748. doi: 10.3969/j.issn.1003-0530.2011.05.016

    LIU Chenglan, GAO Xunzhang, and LI Xiang. Review of interferometric ISAR Imaging[J]. Signal Processing, 2011, 27(5): 737–748. doi: 10.3969/j.issn.1003-0530.2011.05.016
    [43] 李军, 王冠勇, 韦立登, 等. 基于毫米波多基线InSAR的雷达测绘技术[J]. 雷达学报, 2019, 8(6): 820–830. doi: 10.12000/JR19098

    LI Jun, WANG Guanyong, WEI Lideng, et al. Radar mapping technology based on millimeter-wave multi-baseline InSAR[J]. Journal of Radars, 2019, 8(6): 820–830. doi: 10.12000/JR19098
    [44] 田彪, 刘洋, 呼鹏江, 等. 宽带逆合成孔径雷达高分辨成像技术综述[J]. 雷达学报, 2020, 9(5): 765–802. doi: 10.12000/JR20060

    TIAN Biao, LIU Yang, HU Pengjiang, et al. Review of high-resolution imaging techniques of wideband inverse synthetic aperture radar[J]. Journal of Radars, 2020, 9(5): 765–802. doi: 10.12000/JR20060
    [45] MIT. MIT Lincoln Laboratory 2008 Annual Report[R]. 2008.
    [46] FORRESTER N T. Surface reconstruction from interferometric ISAR data[D]. [Master dissertation], Massachusetts Institute of Technology, 2014.
    [47] ZHAO Lizhi, GAO Meiguo, MARTORELLA M, et al. Bistatic three-dimensional interferometric ISAR image reconstruction[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(2): 951–961. doi: 10.1109/TAES.2014.130702
    [48] YUAN Zhengkun, WANG Junling, ZHAO Lizhi, et al. Long orbit arc InISAR imaging of space targets with monostatic radar[J]. IEEE Sensors Journal, 2021, 21(5): 5983–5994. doi: 10.1109/JSEN.2020.3039893
    [49] SHAO Shuai, ZHANG Lei, LIU Hongwei, et al. Images of 3-D maneuvering motion targets for interferometric ISAR with 2-D joint sparse reconstruction[J]. IEEE Transactions on Geoscience and Remote Sensing, in press, 2020.
    [50] MAYHAN J T, BURROWS M L, CUOMO K M, et al. High resolution 3D “snapshot” ISAR imaging and feature extraction[J]. IEEE Transactions on Aerospace and Electronic Systems, 2001, 37(2): 630–642. doi: 10.1109/7.937474
    [51] ZHOU Yejian, ZHANG Lei, CAO Yunhe, et al. Attitude estimation and geometry reconstruction of satellite targets based on ISAR image sequence interpretation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(4): 1698–1711. doi: 10.1109/TAES.2018.2875503
    [52] 王志会, 王壮, 蒋李兵. 基于线特征差分投影的空间目标姿态估计方法[J]. 信号处理, 2017, 33(10): 1377–1384. doi: 10.16798/j.issn.1003-530.2017.10.014

    WANG Zhihui, WANG Zhuang, and JIANG Libing. Pose estimation method for space targets based on the linear features differencing projection[J]. Journal of Signal Processing, 2017, 33(10): 1377–1384. doi: 10.16798/j.issn.1003-530.2017.10.014
    [53] XIE Pengfei, ZHANG Lei, DU Chuan, et al. Space target attitude estimation from ISAR image sequences with key point extraction network[J]. IEEE Signal Processing Letters, 2021, 28: 1041–1045. doi: 10.1109/LSP.2021.3075606
    [54] ZHOU Yejian, ZHANG Lei, and CAO Yunhe. Dynamic estimation of spin spacecraft based on multiple-station ISAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2977–2989. doi: 10.1109/TGRS.2019.2959270
    [55] ZHOU Yejian, ZHANG Lei, CAO Yunhe, et al. Optical-and-radar image fusion for dynamic estimation of spin satellites[J]. IEEE Transactions on Image Processing, 2019, 29: 2963–2976. doi: 10.1109/TIP.2019.2955248
    [56] SUWA K, WAKAYAMA T, and IWAMOTO M. Three-dimensional target geometry and target motion estimation method using multistatic ISAR movies and its performance[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6): 2361–2373. doi: 10.1109/TGRS.2010.2095423
    [57] ZHOU Yejian, ZHANG Lei, and CAO Yunhe. Attitude estimation for space targets by exploiting the quadratic phase coefficients of inverse synthetic aperture radar imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(6): 3858–3872. doi: 10.1109/TGRS.2018.2888631
    [58] ZHOU Yejian, ZHANG Lei, WEI Shaopeng, et al. Dynamic analysis of spin satellites through the quadratic phase estimation in multiple-station radar images[J]. IEEE Transactions on Computational Imaging, 2020, 6: 894–907. doi: 10.1109/TCI.2020.2995052
    [59] LEFFERTS E J, MARKLEY F L, and SHUSTER M D. Kalman filtering for spacecraft attitude estimation[J]. Journal of Guidance,Control,and Dynamics, 1982, 5(5): 417–429. doi: 10.2514/3.56190
    [60] KIM S G, CRASSIDIS J L, CHENG Yang, et al. Kalman filtering for relative spacecraft attitude and position estimation[J]. Journal of Guidance,Control,and Dynamics, 2007, 30(1): 133–143. doi: 10.2514/1.22377
    [61] MARKLEY F L. Attitude error representations for Kalman filtering[J]. Journal of Guidance,Control,and Dynamics, 2003, 26(2): 311–317. doi: 10.2514/2.5048
    [62] OPROMOLLA R and NOCERINO A. Uncooperative spacecraft relative navigation with LIDAR-based unscented Kalman filter[J]. IEEE Access, 2019, 7: 180012–180026. doi: 10.1109/ACCESS.2019.2959438
    [63] CAO Lu, QIAO Dong, and CHEN Xiaoqian. Laplace ℓ1 Huber based cubature Kalman filter for attitude estimation of small satellite[J]. Acta Astronautica, 2018, 148: 48–56. doi: 10.1016/j.actaastro.2018.04.020
    [64] VANDYKE M C, JANA L S, and HALL C D. Unscented Kalman filtering for spacecraft attitude state and parameter estimation[J]. Advances in the Astronautical Sciences, 2004, 118(1): 217–228.
    [65] WENDEL J, MEISTER O, SCHLAILE C, et al. An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter[J]. Aerospace Science and Technology, 2006, 10(6): 527–533. doi: 10.1016/j.ast.2006.04.002
    [66] CAROZZA L and BEVILACQUA A. Error analysis of satellite attitude determination using a vision-based approach[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 83: 19–29. doi: 10.1016/j.isprsjprs.2013.05.007
    [67] NISTÉR D, NARODITSKY O, and BERGEN J. Visual odometry for ground vehicle applications[J]. Journal of Field Robotics, 2006, 23(1): 3–20. doi: 10.1002/rob.20103
    [68] KOUYAMA T, KANEMURA A, KATO S, et al. Satellite attitude determination and map projection based on robust image matching[J]. Remote Sensing, 2017, 9(1): 90. doi: 10.3390/rs9010090
  • 加载中
图(42)
计量
  • 文章访问数:  4556
  • HTML全文浏览量:  1842
  • PDF下载量:  386
  • 被引次数: 0
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

目录

    /

    返回文章
    返回