基于机器学习的弱光条件下卫星激光终端方向和零误差估计。

IF 1.4 3区 物理与天体物理 Q3 OPTICS
Jie Zhang, Yubin Cao, Pengzhen Guo, Zekun Li, Hairui Du, Nanxing Chen, Kairui Cao, Liying Tan
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引用次数: 0

摘要

在卫星光通信终端的装配、发射和在轨运行中,微小的偏差是难以避免的,会导致指向误差,给光通信链路的建立带来挑战。为了估计卫星在轨终端的指向误差,提出了一种基于月球表面图像的定标算法。首先,采用低光图像特征提取算法,对低光图像连续帧进行处理,得到月球表面特征图;然后,将特征映射与误差估计模型相结合,实现了方向误差和零误差的预测;地面验证结果验证了该算法在低信噪比条件下的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of direction and zero errors of satellite laser terminals in low-light conditions based on machine learning.

In the assembly, launch, and on-orbit operation of satellite optical communication terminals, small deviations are difficult to avoid, which can lead to pointing errors and challenges to the establishment of optical communication links. To estimate the pointing errors of on-orbit satellite terminals, a calibration algorithm is developed based on lunar surface imagery. First, a feature extraction algorithm for low-light images is employed to process consecutive frames of low-light images to obtain a lunar surface feature map. Then, by combining the feature map and error estimation model, predictions of direction errors and zero errors were achieved. The ground validation results demonstrate the effectiveness and feasibility of the proposed on-orbit error estimation algorithm under low-signal-to-noise-ratio conditions.

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来源期刊
CiteScore
3.40
自引率
10.50%
发文量
417
审稿时长
3 months
期刊介绍: The Journal of the Optical Society of America A (JOSA A) is devoted to developments in any field of classical optics, image science, and vision. JOSA A includes original peer-reviewed papers on such topics as: * Atmospheric optics * Clinical vision * Coherence and Statistical Optics * Color * Diffraction and gratings * Image processing * Machine vision * Physiological optics * Polarization * Scattering * Signal processing * Thin films * Visual optics Also: j opt soc am a.
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