An end-to-end identification algorithm for smearing star image

doi:10.3390/rs13224541

CIOMP OpenIR

	An end-to-end identification algorithm for smearing star image
	J. Han; X. Yang; T. Xu; Z. Fu; L. Chang; C. Yang and G. Jin
	2021
发表期刊	Remote Sensing
ISSN	20724292
卷号	13 期号:22
摘要	In the previous study, there were a few direct star identification (star-ID) algorithms for smearing star image. An end-to-end star-ID algorithm is proposed in this article, to directly identify the smearing image from star sensors with fast attitude maneuvering. Combined with convolutional neural networks and the self-attention mechanism of transformer encoder, the algorithm can effectively classify the smearing image and identify the star. Through feature extraction and position encoding, neural networks learn the position of stars to generate semantic information and realize the end-to-end identification for the smearing star image. The algorithm can also solve the problem of low identification rate due to smearing of long exposure time for images. A dataset of dynamic stars is analyzed and constructed based on multiple angular velocities. Experiment results show that, compared with representative algorithms, the identification rate of the proposed algorithm is improved at high angular velocities. When the three-axis angular velocity is 10/s, the rate is still 60.4%. At the same time, the proposed algorithm has good robustness to position noise and magnitude noise. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
DOI	10.3390/rs13224541
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收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65216
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	J. Han,X. Yang,T. Xu,et al. An end-to-end identification algorithm for smearing star image[J]. Remote Sensing,2021,13(22).
APA	J. Han,X. Yang,T. Xu,Z. Fu,L. Chang,&C. Yang and G. Jin.(2021).An end-to-end identification algorithm for smearing star image.Remote Sensing,13(22).
MLA	J. Han,et al."An end-to-end identification algorithm for smearing star image".Remote Sensing 13.22(2021).

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