摘要
基于光电跟踪设备对空间目标进行跟踪测量时,由于电磁干扰、云层遮挡或者地影等因素的影响,造成空间目标成像在设备视场中无法提取,严重时甚至导致系统闭环跟踪不能平稳进行。此时可以采用理论引导的方式,利用预测轨迹继续进行跟踪搜索。本文将广泛用于计算机视觉领域特征提取的随机抽样一致性(RANSAC)算法引入轨迹预测,并根据观测数据分布的特点进行改进提出WRANSAC算法,用于实时处理有限的历史观测数据,进行轨迹预测。引入该算法后,在对空间目标轨迹预测时,对历史观测数据的容错能力提高,对模型的敏感性降低,预测结果的准确性和鲁棒性远远优于最小二乘法。通过对比预测轨迹和实际轨迹,证明了该算法的有效性。
When the electro-optic tracking system is used for space target tracking, it is difficult to extract the target from the field of view occasionally due to the impact of electromagnetic interference, cloud cover or earth shadow etc., and the closed-loop tracking system can barely work in severe cases. At this point the predicted orbit can be used to guide the system to ensure smooth scanning and tracking. In this paper, random sample consensus(RANSAC) algorithm is introduced, which has been widely used in feature extraction in computer vision, to achieve higher prediction accuracy. The loss function of RANSAC algorithm is improved and the WRANSAC algorithm is proposed according to the distribution of observed data, which is used to deal with the limited observation data in real time to track the space target. After the algorithm is adopted, the fault tolerance of observation data is improved and the sensitivity of the model is reduced. The accuracy and robustness of the prediction results are much better than that of the least squares method. The validity of the WRANSAC algorithm is proved by the comparison between the predicted trajectory and the actual trajectory.
作者
严灵杰
黄永梅
张涯辉
唐涛
夏运霞
Yan Lingjie;Huang Yongmei;Zhang Yahui;Tang Tao;Xia Yunxia(Key Laboratory of Beam Control,Chinese Academy of Sciences,Chengdu,Sichuan 610209,China;Institute of Optics and Electronics,Chinese Academy of Sciences,Chengdu,Sichuan 610209,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《光电工程》
CAS
CSCD
北大核心
2019年第11期38-44,共7页
Opto-Electronic Engineering
基金
中国科学院空间科学背景型号项目(XDA15020400)~~
