Volume 36 Issue 2
Mar.  2016
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CANG Zhongya, XUE Bingsen, CHENG Guosheng, ZHU Xiaolu. Atmospheric Drag Coefficient Modification for Orbit Prediction Precision Improvement of LEO Space Objects[J]. Chinese Journal of Space Science, 2016, 36(2): 188-195. doi: 10.11728/cjss2016.02.188
Citation: CANG Zhongya, XUE Bingsen, CHENG Guosheng, ZHU Xiaolu. Atmospheric Drag Coefficient Modification for Orbit Prediction Precision Improvement of LEO Space Objects[J]. Chinese Journal of Space Science, 2016, 36(2): 188-195. doi: 10.11728/cjss2016.02.188

Atmospheric Drag Coefficient Modification for Orbit Prediction Precision Improvement of LEO Space Objects

doi: 10.11728/cjss2016.02.188
  • Received Date: 2015-03-09
  • Rev Recd Date: 2015-11-18
  • Publish Date: 2016-03-15
  • Atmospheric drag is the primary disturbing force to LEO space objects since the atmospheric density is still considerable. This paper proposes a new method based on space environment indices and neural network model to modify drag coefficient. According to TLE (Two Line Element) sets, by simulating the orbit prediction and comparing prediction semi-major axis to real-time value, the optimal values of drag coefficients (B0sup*) are selected. It is found that optimal values are one or two days ahead the values in TLE, and they are all corresponded with F10.7 and Ap indices. Based on historic data, the neural network is built for drag coefficient correction to improve the orbit prediction precision. Result shows that the neural network model could timely response to space environment disturbance. This method is applied in Tiangong-1 (TG-1) and International Space Station (ISS) orbit prediction to verify its validity and universality, and it shows that the orbit prediction accuracy is improved by 50%~60% during geomagnetic disturbance while the errors are biggest. Generally, this method could improve the orbit prediction precision by 30%, the and success rate of improvement is about 80%.

     

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  • [1]
    HOOTS F R, ROEHRICH R L. Space Track Report No.3: Models for Propagation of NORAD Element Sets[R]. Peterson: Aerospace Defense Command, United States Air Force, 1980
    [2]
    VALLADO D A, CRAWFORD P, HUJSAK R, et al. Revisiting Spacetrack Report #3[C]. AIAA 2006-6753. AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Keystone, Colorado, 2006
    [3]
    HAN Lei, CHEN Lei, ZHOU Bozhao. Precision analysis of SGP4/SDP4 implemented in space debris orbit prediction[J]. Chin. Space Sci. Tech., 2004, 4:65-71 (韩蕾, 陈磊, 周伯昭. SGP4/SDP4模型用于空间碎片轨道预测的精度分析[J]. 中国空间科学技术, 2004, 4:65-71)
    [4]
    WANG R, LIU J, ZHANG Q M. Propagation errors analysis of TLE data[J]. Adv. Space Res., 2009, 43:1065-1069
    [5]
    YAN Ruidong, WANG Ronglan, LIU Siqing, et al. Study of covariance calculation in space objects collision warning[J]. Chin. J. Space Sci., 2014, 34(4):441-448 (闫瑞东, 王荣兰, 刘四清, 等. 空间目标碰撞预警的协方差计算与应用[J]. 空间科学学报, 2014, 34(4):441-448)
    [6]
    WEI D, ZHAO C Y. Analysis on the accuracy of the SGP4/SDP4 model[J]. Astron. Sin., 2009, 50(3):332-339 (韦栋, 赵长印. SGP4/SDP4模型精度分析[J]. 天文学报, 2009, 50(3):332-339)
    [7]
    LIU Wei, MIAO Yuanxing. Test of the accuracies of SGP4/SDP4 model predictions[J]. Astron. Res. Tech., 2011, 8(2):128-131 (刘卫, 缪元兴. SGP4/SDP4模型预报可靠性分析[J]. 天文研究与技术, 2011, 8(2):128-131)
    [8]
    LEVIT C, MARSHALL W. Improved orbit predictions using two-line elements[J]. Adv. Space Res., 2011, 47:1107-1115
    [9]
    BENNETT J C, SANG J, SMITH C, et al. Improving low-Earth orbit predictions using two-line element data with bias correction[C]//Advanced Maui Optical and Space Surveillance Technologies Conference. Maui, Hawaii: The Maui Economic Development Board, 2012
    [10]
    LIU Wei, WANG Ronglan, LIU Siqing, et al. TLE prediction accuracy improvement and its application in collision warning[J]. Chin. J. Space Sci., 2014, 34(4):449-459 (刘卫, 王荣兰, 刘四清, 等. TLE预报精度改进及碰撞预警中的应用[J]. 空间科学学报, 2014, 34(4):449-459)
    [11]
    YIN Fan, MA Shuying, LI Jing, et al. Simulation of orbit decay for LEO satellites caused by atmospheric drag[J]. Chin. J. Geophys., 2013, 56(12):3980-3987 (尹凡, 马淑英, 李晶, 等. 大气阻力引起卫星轨道衰减的数值模拟[J]. 地球物理 学报, 2013, 56(12):3980-3987)
    [12]
    LIU Shushi, GONG Jiancun, LIU Siqing Q, et al. Atmospheric drag coefficient calibration in medium-term orbit prediction[J]. Chin. J. Astron., 2013, 34(2):157-162 (刘舒莳, 龚建村, 刘四清, 等. 中长期轨道预报中大气阻力系数补偿算法的研究[J]. 宇航学报, 2013, 34(2):157-162)
    [13]
    LIU H, LÜHR H. Strong disturbance of the upper thermospheric neutral density due to magnetic storms: CHAMP observations[J]. J. Geophys. Res., 2005, 110, A09S29. DOI:10.1029/2004, JA01090
    [14]
    WILLIS P, DELEFLIE F, BARLIER F, et al. Effects of thermosphere total density perturbations on LEO orbits during severe geomagnetic conditions (Oct.-Nov. 2003) using DORIS and SLR data[J]. Adv. Space Res., 2005, 36:522-533
    [15]
    ZHANG Longfei, XUE Bingsen. Application of BP neural network in prediction of proton events peak flux[J]. Chin. J. Space Sci., 2007, 27(1):19-22 (张龙飞, 薛炳森. 应用BP神经网络针对高通量质子事件的通量数值预报[J]. 空间科学学报, 2007, 27(1):19-22)
    [16]
    LI X J, ZHOU J H, GUO R. High-precision orbit prediction and error control techniques for COMPASS navigation satellite[J]. Chin. Sci. Bull., 2014, 59:2841-2849
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