Volume 45 Issue S1
Jun.  2016
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Zhai Guang, Zhao Qi, Zhang Jingrui. On-board space debris recognition and accurate positioning method[J]. Infrared and Laser Engineering, 2016, 45(S1): 169-176. doi: 10.3788/IRLA201645.S129001
Citation: Zhai Guang, Zhao Qi, Zhang Jingrui. On-board space debris recognition and accurate positioning method[J]. Infrared and Laser Engineering, 2016, 45(S1): 169-176. doi: 10.3788/IRLA201645.S129001

On-board space debris recognition and accurate positioning method

doi: 10.3788/IRLA201645.S129001
  • Received Date: 2016-01-05
  • Rev Recd Date: 2016-02-03
  • Publish Date: 2016-05-25
  • A method of detecting and recognizing space debris based on visible light camera and laser range finder was proposed in this paper. The shape of imaging was determined by the relative velocity, and distance of space debris. In order to matching different images, an ellipse that had the same second-order central moment was adopted to describe the edge of image. Based on the features of ellipse, the rules of matching images will be established. By matching different images, the coordinate and azimuth angles can be calculated. If only the azimuth angles were available, the relative position-velocity filter was used for guiding the laser range finder. When the laser range finder worked properly, the extend-Kalman filter was used for getting accurate movement information of the target.
  • [1] Bai Xianzong. Research on orbital prediction error and collision probability of space objects[D]. Changsha:National University of Defense Technology, 2013. (in Chinese) 白显宗. 空间目标轨道预报误差与碰撞概率问题研究[D]. 长沙:国防科学技术大学, 2013.
    [2] Letizia F, Colombo C, Lewis H G. Analytical model for the propagation of small-debris-object clouds after fragmentations[J]. Journal of Guidance, Control, and Dynamics, 2015, 38(8):1478-1491.
    [3] Jin Yuzhu. Research on optical detection and recognition method of space de-bris[D]. Harbin:Harbin Institute of Technology, 2007. (in Chinese) 金玉竹. 空间碎片光学探测与识别方法研究[D]. 哈尔滨:哈尔滨工业大学, 2007.
    [4] Hao Yingming, Zhu Feng, Ou Jinjun. 3D visual methods for object pose measurement[J]. Journal of Image and Graphics, 2002, 12:26-30. (in Chinese) 郝颖明, 朱枫, 欧锦军. 目标位姿测量中的三维视觉方法[J]. 中国图象图形学报, 2002, 12:26-30.
    [5] Cai Han. Experiment research of non-cooperative space target relative measurement based on binocular vision[D]. Beijing:Beijing Institute of Technology, 2015. (in Chinese) 蔡晗. 基于双目视觉的非合作目标相对测量实验研究[D].北京:北京理工大学, 2015.
    [6] Pan Haibin, Cong Mingyu, Zhang Wei, et al. Imaging model study of space objects from space remote sensor[J]. Journal of Harbin Institute of Technology, 2008, 40(11):1699-1702. (in Chinese) 潘海斌, 丛明煜, 张伟, 等. 航天遥感器的空间目标成像模型研究[J]. 哈尔滨工业大学学报, 2008, 40(11):1699-1702.
    [7] Canny J. A computational approach to edge detection[J]. Pattern Analysis Machine Intelligence IEEE Transactions on, 1986, 8(6):679-698.
    [8] Hu M K. Visual pattern recognition by moment invariants[J]. IRE Transactions on Information Theory, 1962, 8(2):179-187.
    [9] Sun Bei. Research on image recognition based on moment features[D]. Taiyuan:Taiyuan University of Technology, 2010. (in Chinese) 孙贝. 基于矩特征提取的图像识别算法研究[D]. 太原:太原理工大学, 2010.
    [10] Hu Haitao, Ping Ziliang, Wu Bin. Quick algorithm of image moments with rotational invariance[J]. Acta Optica Sinica, 2010, 30(2):394-398. (in Chinese) 胡海涛, 平子良, 吴斌. 具有旋转不变性的图像矩的快速算法[J]. 光学学报, 2010, 30(2):394-398.
    [11] Zhai Guang, Zhang Jingrui. Research on rapid attitude tracking for space non-cooperative target[J]. Journal of Astronautics, 2013, 34(3):362-368. (in Chinese) 翟光,张景瑞. 空间非合作目标快速姿态跟踪导航方法研究[J]. 宇航学报, 2013, 34(3):362-368.
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On-board space debris recognition and accurate positioning method

doi: 10.3788/IRLA201645.S129001
  • 1. School of Aerospace Engineering,Beijing Institute of Technology,Beijing 100081,China

Abstract: A method of detecting and recognizing space debris based on visible light camera and laser range finder was proposed in this paper. The shape of imaging was determined by the relative velocity, and distance of space debris. In order to matching different images, an ellipse that had the same second-order central moment was adopted to describe the edge of image. Based on the features of ellipse, the rules of matching images will be established. By matching different images, the coordinate and azimuth angles can be calculated. If only the azimuth angles were available, the relative position-velocity filter was used for guiding the laser range finder. When the laser range finder worked properly, the extend-Kalman filter was used for getting accurate movement information of the target.

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