摘要
在短弧观测条件下通过密集角度数据进行初轨确定时,一般通过光学相机对同一区域进行连续曝光以获取角速度数据,这对探测器的性能提出了严格要求,并相应的增加了观测成本。首先,采用空间滤波法将调制的时域亮度信号转化为频谱信息,通过提取频谱次峰频率大小,并结合稀疏的角度数据,实现目标的角速度测量,进而降低了观测成本;其次,针对10 298个低轨空间碎片样本,通过统计低轨空间碎片的半长轴和离心率分布,总结了低轨碎片的轨道参数分布。在此基础上,结合测量的角度信息和角速度信息,构建基于离心率评价的适值函数,通过在距离-距离变化率的解空间内利用遗传算法对适值函数进行优化实现目标初始轨道的确定,通过对NORAD(North American Aerospace Defense Command)编号分别为52 066、29 734、33 953和47 074的四个目标进行成像仿真验证,结果表明半长轴误差分别为-56.60 km、-72.90 km、-5.71 km和-109.88 km,离心率误差分别为-0.007 421、-0.040 02、0.001 103和0.005 546,轨道倾角误差分别为0.557°、0.122°、-0.521°以及-0.769°,体现了该方法具有一定的可靠性,能够实现目标的初轨确定。
Objective Space debris mainly refers to all man-made objects except for normal spacecraft,including various satellites that have completed their missions,rocket bodies,waste in the process of performing space missions,and debris generated by the collision of space objects.These debris pose a great threat to the safety of spacecraft in orbit.With the continuous development of science and technology,space activities are becoming more and more frequent,which has led to an increasing number of space debris,posing a serious threat to the safety of spacecraft in orbit.Therefore,in order to reduce the impact of space debris on spacecraft,it is particularly important to carry out orbital monitoring and prediction of debris.Optical cameras play an important role in the field of space debris detection with their advantages of low energy consumption,high resolution and wide field of view coverage.Traditional initial orbit determination algorithms such as the Laplace method and the Gauss method are difficult to achieve the initial orbit determination of targets under short arc conditions due to the large error influence under short arc conditions.Some new methods based on dense data require optical cameras to continuously shoot targets.On the one hand,a large amount of data increases the burden on the system.On the other hand,continuous exposure of high-pixel optical cameras will cause overheating problems and affect the stability of the camera.Therefore,this paper proposes to use spatial filtering method to measure the angular velocity of the target,build the corresponding fitness function based on sparse angle data,and use genetic algorithm to optimize the initial orbit determination of the target.Methods This paper simulates and verifies this method through simulation imaging.First,the orbital parameter distribution of the current space debris is statistically analyzed(Fig.2-Fig.3).Then a simulation observation model is established in this paper(Fig.4).The target is detected by the observation equipment,and a part is received by the high-precision and low-exposure frequency imaging detector,which records the images of the target at three moments:when it enters the field of view,in the field of view,and before it leaves the field of view(Fig.6).The angle information of the target at these three moments is obtained through astronomical positioning,and the other part is filtered through a filter(Fig.1).The high-frequency simulation image is convolved with the sine filter to obtain the time domain brightness signal of the target,and is focused on the photometric sensor through the lens.At this time,the photometric sensor only receives the brightness information of the target(Fig.7).By optimizing the fitness function using a genetic algorithm,the orbital parameter error of the target is obtained(Tab.6)Results and Discussions By simulating four low-orbit targets,the target angular velocity error is within 5%through the spatial filtering method(Tab.3).The fitness function is optimized by genetic algorithm,and the distribution of the fitness function in the solution space is obtained(Fig.8).The results show that the relative errors of the distance between the detector and the target are 1.94%,0.00%,0.78%and 1.57%,respectively,and the distance measurement error is less than 40 km;the relative errors of the distance change rate are 6.25%,6.42%,8.01%,4.12%(Tab.5),respectively,and the measurement error of the distance change rate is less than 200 m/s,which shows that this method has good ranging accuracy.By solving the target position and velocity information,the target orbit parameter error(Tab.6)is obtained,the semi-major axis error is less than 110 km,the eccentricity error is less than 0.05,and the orbit inclination error is less than 0.8°.Compare the results with the Laplace method and the Gauss method(Tab.7).This method shows good initial orbit determination accuracy for low-orbit targets.Conclusions This paper proposes a method of using spatial filtering velocimetry to measure angular velocity and combine sparse angle numbers to determine the initial orbit of the target.This method uses continuous timedomain brightness signals and a small amount of angle information.Compared with the traditional method of continuously shooting the target with an optical camera to obtain angle information,this method effectively reduces the amount of data for initial orbit determination and reduces the workload of the optical camera.Secondly,by statistically analyzing the orbital parameter distribution of low-orbit space debris,the results show that the semi-axis length of most space debris is between 6800 km and 8000 km,and the eccentricity is concentrated within 0.05.Based on this,the evaluation of eccentricity is added to the fitness function,and the simulation of four targets is verified.The results show that the semi-major axis error of the four targets is less than 110 km,the eccentricity error is less than 0.05,and the orbit inclination error is less than 0.8°,which shows that the initial orbit determination accuracy of low eccentricity orbit targets is better.The reason is that the evaluation of eccentricity is added to the fitness function,which enhances the convergence of the fitness function and suppresses the ambiguity of the solution to a certain extent.However,this method is mainly applicable to loworbit,low-eccentricity targets.In the future,this method will be further improved to expand the scope of applicable targets and provide more extensive support for space debris orbit determination and target situation awareness.
作者
裴韩
王久龙
邢妍
牟帅威
李锦峰
柳乐
蔡盛
PEI Han;WANG Jiulong;XING Yan;MU Shuaiwei;LI Jinfeng;LIU Le;CAI Sheng(Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China;University of Chinese Academy of Science,Beijing 100049,China)
出处
《红外与激光工程》
北大核心
2025年第7期353-363,共11页
Infrared and Laser Engineering
基金
长春市科技发展计划项目(2024GZZ18)。
关键词
初轨确定
光学测角
空间滤波测速法
遗传算法
空间碎片
initial orbit determination
optical angle measurement
spatial filter velocimetry
genetic algorithm
space debris
