基于相机阵列的空间目标初轨确定方法  

Initial orbit determination method of space target based on camera array

作　　者：李春阳 张廷华 李迎春 LI Chunyang;ZHANG Tinghua;LI Yingchun(Space Engineering University,Beijing 101416,China;96945 Troops,Baoding 072653,China)

机构地区：[1]航天工程大学,北京101416 [2]96945部队,河北保定072653

出　　处：《电子设计工程》2023年第9期94-98,共5页Electronic Design Engineering

摘　　要：相机阵列是空间目标监视和探测识别的重要手段,具有大视场、高动态以及多通道的特点,可应用于空间目标的广域监视、初始轨道确定等态势感知任务。针对相机阵列观测空间目标获取的短弧、甚短弧观测数据难以实现空间目标的快速初轨确定问题,利用共轭梯度(CG)快速求解单位矢量(UVM),并以此初轨确定结果作为粒子群算法的初始值,利用基于粒子群的改进单位矢量初轨确定方法,克服粒子群算法对初始值敏感的缺陷。通过实验验证,基于共轭梯度的单位矢量法与传统单位矢量法相比,空间目标初轨确定速度有较大提高,且基于粒子群的改进单位矢量法与传统单位矢量法相比,空间目标半长轴估计精度明显提高。Camera array is an important means of space target monitoring,detection and recognition.It has the characteristics of large field of view,high dynamic and multi⁃channel.It can be applied to situation awareness tasks such as wide area monitoring and initial orbit determination of space targets.Aiming at the problem that it is difficult to determine the fast initial orbit of space target by using the short arc and very short arc observation data obtained by camera array observation,the Unit Vector Method(UVM)is quickly solved by using the Conjugate Gradient(CG)method,and the initial orbit determination result is used as the initial value of particle swarm optimization algorithm,and the improved unit vector initial orbit determination method based on particle swarm optimization is used.Overcome the defect that particle swarm optimization algorithm is sensitive to initial value.Experiments show that compared with the traditional unit vector method,the unit vector method based on conjugate gradient method has a great improvement in the speed of space target initial orbit determination,and the improved unit vector method based on particle swarm optimization has a significant improvement in the estimation accuracy of space target semi major axis compared with the traditional unit vector method.

关 键 词：初轨确定 相机阵列 共轭梯度 粒子群优化算法 

分 类 号：TN29[电子电信—物理电子学]