Dangerous Conjunction Analysis Of Space Objects Based On Random Point Simulation Method
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摘要: 基于SGP4模型在空间目标轨道预报中的应用, 在预报的位置速度信息和误差 信息基础上, 提出一种空间两目标碰撞预警的分析方法, 即随机点模拟方法. 与传统的交会平面积分方法相比, 其主要有两点不同: 一是在误差信息中考虑 了误差均值的影响, 即误差椭球不再以预报位置为中心分布; 二是在分析方 法上侧重于真实模拟可能的交会情形, 而不忽略任一方向上的误差. 通过算例分 析验证了该方法的可行性, 结果表明误差均值的非零性使得最大碰撞概率不 一定出现在预报的最近交会距离时刻. 同时仿真结果还表明, 两目标在相对速 度方向上的相对位置仍然存在误差, 这可能造成随机点模拟的碰撞概率计算 值较交会平面积分方法偏小. 不同的碰撞预警分析方法对应不同的预警门限, 根据文中实例, 初步确定10-6为随机点模拟方法的红色预警值.Abstract: The position, velocity and prediction error information of space objects can be obtained by using two-line element set and SGP4 model. Based on these results, a new method to calculate the collision probability is proposed, which is called the random point simulation method. There are two differences when this new method is compared with the traditional method of integral in conjunction plane. One is to concern the effects of error bias, which means the error ellipsoid no longer center on the predicted position. The other is to focus on simulating all possible conjunction situations and do not ignore error in each direction. The feasibility of this method is verified by analyzing cases, and results show that the maximum collision probability no longer appears in the time of closest approach because the error bias is not zero. Meanwhile, simulation results indicate that the positional relationship between two objects has also deviation in the direction of relative velocity, so the collision probability by random point simulation method is smaller than that of integral method. Different collision warning methods correspond to different warning thresholds, and 10-6 can be determined as the warning threshold of random point simulation method based on the case analysis in this paper.
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Key words:
- TLEs /
- SGP4 Model /
- Error ellipsoid /
- Collision warning
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[1] Liu Jing, wang Ronglan, Zhang Hongbo, et al. Space debris collision prediction research[J]. Chin. J. Space Sci., 2004, 24(6):462-469. In Chinese (刘静, 王荣兰, 张宏博, 等. 空间碎片碰撞预警研究[J]. 空间科学学报, 2004, 24(6):462-469) [2] 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 [3] Vallado D A, Crawford P, Hujsak R, et al. Revisiting Spacetrack Report #3[R], AIAA 2006-6753. Keystone, Colorado: AIAA/AAS Astrodynamics Specialist Confe-rence and Exhibit, 2006 [4] Yang Zhitao, Liu Lin, Liu Jing, et al. A high efficiency orbit screening method for space debris collision prediction[J]. Chin. J. Space Sci., 2013, 33(2):176-181. In Chinese (杨志涛, 刘林, 刘静, 等. 空间目标碰撞预警中的一种高效筛选方法[J]. 空间科学学报, 2013, 33(2):176-181) [5] Bai Xianzong, Chen Lei, Zhang Yi, Tang Guojin. Survey on collision assessment and warning techniques for space object[J]. J. Astron., 2013, 34(8):1027-1039. In Chinese (白显宗, 陈磊, 张翼, 唐国金. 空间目标碰撞预警技术研究综述[J]. 宇航学报, 2013, 34(8):1027-1039) [6] Akella M R, Alfriend K T. The probability of collision between space objects[J]. J. Guid. Contr. Dyn., 2000, 23(5):9-10, 769-772 [7] Cheng Tao, Liu Jing, Wang Ronglan, Yu Youcheng. Collision probability analysis and application of cataloged linebreak space debris[J]. Chin. J. Space Sci., 2006, 26(6):452-458. In Chinese (程陶, 刘静, 王荣兰, 于有成. 空间碎片预警中的碰撞概率方法研究[J]. 空间科学学报, 2006, 26(6):452-458) [8] Rong Jili, Qi Yue, Chen Xiangyu. Accuracy and effec-tiveness analysis of SGP4 implemented in space debris collision alert[J]. Trans. Beijing Inst. Tech., 2013, 33(12):1309-1312. In Chinese (荣吉利, 齐跃, 谌相宇. SGP4模型用于空间目标碰撞预警的 准确性与有效性分析[J]. 北京理工大学学报, 2013, 33(12):1309-1312) [9] Bai Xianzong, Chen Lei. Study of collision probability calculation for space object[J]. J. Astron., 2008, 29(4):1435-1442. In Chinese (白显宗, 陈磊. 空间目标碰 撞概率计算方法研究[J]. 宇航学报, 2008, 29(4):1435-1442) [10] Yan Ruidong, Wang Ronglanm, Liu Siqing, Liu Wei, Gong Jiancun. Study of covariance calculation in space objects collision warning[J]. Chin. J. Space Sci., 2014, 34(4):441-448. In Chinese (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) -
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