Luo Hao, Yindun Mao, Yong Yu, et al. A method of GEO targets recognition in wide-field opto-electronic telescope observation[J]. Opto-Electronic Engineering, 2017, 44(4): 418-426. doi: 10.3969/j.issn.1003-501X.2017.04.006
Citation: Luo Hao, Yindun Mao, Yong Yu, et al. A method of GEO targets recognition in wide-field opto-electronic telescope observation[J]. Opto-Electronic Engineering, 2017, 44(4): 418-426. doi: 10.3969/j.issn.1003-501X.2017.04.006

A method of GEO targets recognition in wide-field opto-electronic telescope observation

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  • In order to carry out the monitoring experiment of Geo-synchronous orbit (GEO) targets, Shanghai Astronomical Observatory developed an equipment with 100-square-degree field of view, called "optical prototype of Geo-synchronous orbit dynamic monitoring system". There are a large number of targets in the field of view, how to recognize the GEO targets effectively from the complex observation images is the focus of this paper. GEO targets appear motionless, at a fixed position in the sky, to ground observers. Due to the earth rotation, stars move at a speed of 15"/s relative to the ground observers. We propose the combination of frame difference method and track correlation method. Frame difference method is used to remove a large number of stars from the images, and track correlation method is used to confirm the GEO targets and connect them from different images. The feasibility and accuracy of the method are verified by the analyses of the observation data. The method can recognize more than 50 GEO targets in the field of view at the same time, and the recognition accuracy exceeds 95%.
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  • [1] 吴连大.人造卫星与空间碎片的轨道和探测[M].北京:中国科学技术出版社, 2012: 264.

    Google Scholar

    Wu Lianda. Track and detection of satellites and space debris[M]. Beijing: Science and Technology of China Press, 2012: 264.

    Google Scholar

    [2] Molotov I, Agapov V, Titenko V, et al. International scientific optical network for space debris research[J]. Advances in Space Research, 2008, 41(7): 1022-1028. doi: 10.1016/j.asr.2007.04.048

    CrossRef Google Scholar

    [3] 李东源.国外的地基对空间目标光电探测系统浅析[J].光电对抗与无源干扰, 2003(1): 9-11.

    Google Scholar

    Li Dongyuan. The foreign ground-based electro-optic detecting system to the space targets[J]. Electro-Optic Warfare & Radar Passive Countermeasures, 2003(1): 9-11.

    Google Scholar

    [4] Jeas W C, Anctil R. The ground-based electro-optical deep space surveillance /GEODSS/ system[J]. Military Electronics/Countermeasures, 1981, 7: 47-51.

    Google Scholar

    [5] 罗浩, 毛银盾, 于涌, 等.地球同步轨道带动态监视光学系统样机及试观测结果[J].空间科学学报, 2017, 37(3). DOI: 10.11728/ cjss2017.03.350.

    CrossRef Google Scholar

    [6] 吴功友, 王家松, 刘芳, 等. 利用长期TLE数据判定同步轨道卫星状态[C]//第四届中国卫星导航学术年-S3精密定轨与精密定位, 2013.

    Google Scholar

    Wu Gongyou, Wang Jiasong, Liu Fang, et al. Determine GEO satellite statues with long term TLE data[C]// China Satellite Navigation Conference, 2013.http://cpfd.cnki.com.cn/Article/CPFDTOTAL-WXDH201305003029.htm

    Google Scholar

    [7] 张晓祥. 空间目标光学观测研究[D]. 北京: 中国科学院研究生院, 2007.http://www.irgrid.ac.cn/handle/1471x/656939

    Google Scholar

    [8] 孙荣煜, 赵长印. GEO空间碎片的光学观测与精密定位[J].天文学进展, 2012, 30(3): 394-410.

    Google Scholar

    Sun Rongyu, Zhao Changyin. Optical survey technique for space debris in GEO[J]. Progress in Astronomy, 2012, 30(3): 394-410.

    Google Scholar

    [9] 黄宗福, 孙刚, 陈曾平.空间目标检测序列图像中恒星目标抑制[J].中国图象图形学报, 2013, 18(7): 799-804. doi: 10.11834/jig.20130709

    CrossRef Google Scholar

    Huang Zongfu, Sun Gang, Chen Zengping. Stellar targets suppression in image sequences for space targets detection[J]. Journal of Image and Graphics, 2013, 18(7): 799-804. doi: 10.11834/jig.20130709

    CrossRef Google Scholar

    [10] Chi Jiannan, Fu Ping, Wang Dongshu, et al. A detection method of infrared image small target based on order morphology transformation and image entropy difference[C]// Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China, 2005, 8: 5111-5116.http://www.researchgate.net/publication/4184890_Detection_method_of_infrared_image_small_target_based_on_order_morphology_transformation_and_image_entropy_difference

    Google Scholar

    [11] 李仪芳, 刘景琳.基于连通域算法的区域测量[J].科学技术与工程, 2008, 8(9): 2492-2494.

    Google Scholar

    Li Yifang, Liu Jinglin. Measurement for area based on connected regions arithmetic[J]. Science Technology and Engineering, 2008, 8(9): 2492-2494.

    Google Scholar

    [12] Tzannes A P, Brooks D H. Detecting small moving objects using temporal hypothesis testing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(2): 570-586. doi: 10.1109/TAES.2002.1008987

    CrossRef Google Scholar

    [13] Blostein S D, Huang T S. Detecting small, moving objects in image sequences using sequential hypothesis testing[J]. IEEE Transactions on Signal Processing, 1991, 39(7): 1611-1629. doi: 10.1109/78.134399

    CrossRef Google Scholar

  • Abstract: Geo-synchronous orbit (GEO) has been highly valued because of the increase of satellite launch activities and the limit of the orbital slots. In order to protect space activities in our exclusive orbit space, it is necessary to carry out the dynamic monitoring of Geo-synchronous orbit. Shanghai Astronomical Observatory developed an equipment with 100-square-degree field of view, called “optical prototype of Geo-synchronous orbit dynamic monitoring system”. The prototype was set up in Gaomeigu observation site in Lijiang. Observation experiment was carried out from December 2015 to February 2016. There are a large number of targets including GEO targets and stars in the field of view. The movement forms of GEO targets are various, including satellites working on orbit, new satellites entering orbit, orbit maneuver and deorbit. Some GEO targets with an inclination not equal to 0 degree move at a very low speed due to the Earth perturbation. Effective recognition of the GEO targets from the complex observation images is the foundation of the monitoring activity, and it is also the focus of this paper. GEO targets have an orbital period equal to the Earth‘s rotational period and thus appear motionless, at a fixed position in the sky, to ground observers. Due to the earth rotation, stars move at a speed of 15 "/s relative to the ground observers. Therefore, stars move far more quickly in the observation images than the GEO targets, and we can distinguish them by their different forms of movement. We propose the combination of frame difference method and track correlation method to recognize the GEO targets. Frame difference method is used to remove a large number of stars from the images. Then, we compare the images frame by frame, build the track and update it constantly. If the number of the images in one track reaches a certain amount, we can confirm that target in this track is GEO target. So we can use track correlation method to confirm the GEO targets and connect them from different images. This paper will introduce the applications of the method in detail. The feasibility and accuracy of the method are verified by the analyses of the observation data. The method can recognize more than 50 GEO targets in the field of view at the same time, and the recognition accuracy exceeds 95%.

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