Satellite pose estimation network based on dual-channel ResNet50

YuJing Wang; RuiDa Ye; Tian Zhang; Yue Zhao; ShengHua Zhou; ZhiTao Wang

doi:10.1117/12.2671305

16 March 2023 Satellite pose estimation network based on dual-channel ResNet50

YuJing Wang, RuiDa Ye, Tian Zhang, Yue Zhao, ShengHua Zhou, ZhiTao Wang

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125930S (2023) https://doi.org/10.1117/12.2671305
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

In the satellite pose estimation problem, the deep learning method is used to train the network. The satellite pose needs to estimate the rotation (R) and translation (T), which are difficult to be well estimated simultaneously due to the internal coupling interaction. To solve the above problems, a dual-channel satellite pose estimation network based on ResNet50 is proposed to decouple the rotation and translation of satellite, effectively avoid the interaction, and estimate the translation and rotation of satellite respectively through the constructed network, which improves the recognition effect of satellite attitude. Through experimental verification, the network model constructed in this paper has better effect on the estimation of rotation and translation compared with other methods.

Citation Download Citation

YuJing Wang, RuiDa Ye, Tian Zhang, Yue Zhao, ShengHua Zhou, and ZhiTao Wang "Satellite pose estimation network based on dual-channel ResNet50", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125930S (16 March 2023); https://doi.org/10.1117/12.2671305

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KEYWORDS

Pose estimation

Satellites

Detection and tracking algorithms

Education and training

Deep learning

Feature extraction

Image resolution

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