复杂光照条件下基于鲁棒特征点提取的卫星帆板相对位姿估计

doi:10.12066/j.issn.1007-2861.2671

上海大学学报(自然科学版) ›› 2025, Vol. 31 ›› Issue (3): 516-529.doi: 10.12066/j.issn.1007-2861.2671

复杂光照条件下基于鲁棒特征点提取的卫星帆板相对位姿估计

况亦晗¹, 李冠壹¹, 王正¹, 常亮², 曾丹¹

1. 上海大学通信与信息工程学院, 上海 200444;
2. 中国科学院微小卫星创新研究院, 上海 201304

收稿日期:2025-03-17 出版日期:2025-06-30 发布日期:2025-07-22
通讯作者: 曾丹(1982-),女,教授,博士生导师,博士,研究方向为图像处理、计算机视觉等. E-mail:dzeng@shu.edu.cn
基金资助:
国家自然科学基金资助项目(62372284)

Relative position and attitude estimation of satellite solar panels under complex lighting conditions via robust feature-point extraction

KUANG Yihan¹, LI Guanyi¹, WANG Zheng¹, CHANG Liang², ZENG Dan¹

1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China;
2. Innovation Academy for Microsatellites of Chinese Academy of Science, Shanghai 201304, China

Received:2025-03-17 Online:2025-06-30 Published:2025-07-22

摘要/Abstract

摘要： 卫星帆板相对位姿估计是航天领域的核心技术,对于顺利开展在轨维护任务至关重要.然而,在太空复杂光照条件下,受限于非均匀光照成像和边缘纹理干扰,帆板特征点难以准确获取,从而影响相对位姿精度.因此,提出一种复杂光照条件下基于鲁棒特征点提取的卫星帆板相对位姿估计方法.首先,采用轻量化多尺度边缘引导网络精准分割帆板区域;随后,对预处理的分割结果进行边缘直线拟合和交点计算,实现特征点的有效提取;最后,利用相邻帧信息进行点对匹配,获取帆板的相对位姿参数.实验结果表明,在复杂光照条件下,所提出方法能够有效满足在相机从60 m至15 m的动态抵近过程中,帆板相对姿态误差始终保持在2°以内,相对位置误差由0.38 m逐步减小至0.04 m,具有较高的精度和鲁棒性.

关键词: 图像分割, 特征点提取, 卫星帆板, 位姿估计

Abstract: As a critical technology in the aerospace field, estimating the relative position and attitude of satellite solar panels is crucial for successfully executing on-orbit satellite maintenance missions. However, under complex lighting conditions in space, nonuniform illumination and interference from repetitive edge textures complicate the accurate extraction of solar panel feature points, thereby impacting the precision of relative position and attitude estimation. Therefore, a method for estimating the relative positions and attitudes of satellite solar panels under complex lighting conditions through robust feature-point extraction was proposed. This method began by accurately segmenting the solar panel areas using a lightweight, multiscale edge-guided network. After preprocessing the segmentation results, the edges were fitted to straight lines, and the intersection points of these lines were calculated to efficiently extract the feature points of the solar panels.Based on this information, the relative position and attitude parameters of the solar panels were determined by matching point pairs based on adjacent frame data. Experimental results demonstrate that, under complex lighting conditions, as the camera dynamically approaches from a distance of 60 to 15 m, the proposed method effectively maintained the relative attitude error within 2° and reduced the relative position error from 0.38 to 0.04 m,highlighting its high precision and robustness.

Key words: image segmentation, feature point extraction, satellite solar panels, position and attitude estimation

中图分类号:

况亦晗, 李冠壹, 王正, 常亮, 曾丹. 复杂光照条件下基于鲁棒特征点提取的卫星帆板相对位姿估计[J]. 上海大学学报(自然科学版), 2025, 31(3): 516-529.

KUANG Yihan, LI Guanyi, WANG Zheng, CHANG Liang, ZENG Dan. Relative position and attitude estimation of satellite solar panels under complex lighting conditions via robust feature-point extraction[J]. Journal of Shanghai University（Natural Science Edition）, 2025, 31(3): 516-529.

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复杂光照条件下基于鲁棒特征点提取的卫星帆板相对位姿估计

Relative position and attitude estimation of satellite solar panels under complex lighting conditions via robust feature-point extraction

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