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Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking

文献类型：期刊论文

作者Wang, Lei1,4; Zhang, Xiaoming1,4; Bai, Chunhai3; Xie, Haiwen2,4; Li, Juan1,4; Ge, Jiayi1,4; Wang, Jianfeng1,4; Zeng, Xianqun1; Sun, Jiantao3; Jiang, Xiaojun1,4
刊名MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
出版日期2024-09-18
卷号534期号:1页码:385-399
关键词methods: data analysis techniques: image processing planets and satellites: detection
ISSN号0035-8711
DOI10.1093/mnras/stae2073
产权排序3
英文摘要Optically observing and monitoring moving objects, both natural and artificial, is important to human space security. Non-sidereal tracking can improve the system's limiting magnitude for moving objects, which benefits the surveillance. However, images with non-sidereal tracking include complex background, as well as objects with different brightness and moving mode, posing a significant challenge for accurate multi-object detection in such images, especially in wide field-of-view telescope images. To achieve a higher detection precision in a higher speed, we proposed a novel object detection method, which combines the source feature extraction and the neural network. First, our method extracts object features from optical images such as centroid, shape, and flux. Then, it conducts a naive labelling based on those features to distinguish moving objects from stars. After balancing the labelled data, we employ it to train a neural network aimed at creating a classification model for point-like and streak-like objects. Ultimately, based on the neural network model's classification outcomes, moving objects whose motion modes consistent with the tracked objects are detected via track association, while objects with different motion modes are detected using morphological statistics. The validation, based on the space objects images captured in target tracking mode with the 1-m telescope at Nanshan, Xinjiang Astronomical Observatory, demonstrates that our method achieves 94.72 per cent detection accuracy with merely 5.02 per cent false alarm rate, and a processing time of 0.66 s per frame. Consequently, our method can rapidly and accurately detect objects with different motion modes from wide-field images with non-sidereal tracking.
WOS关键词SPACE-DEBRIS ; WIDE-FIELD ; ALGORITHMS ; ASTROMETRY ; PHOTOMETRY ; TARGETS ; FAINT
资助项目National Science and Technology Major Project[2022ZD0117401] ; National Natural Science Foundation of China[12273063]
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:001315413300006
出版者OXFORD UNIV PRESS
资助机构National Science and Technology Major Project ; National Natural Science Foundation of China
源URL[http://ir.xao.ac.cn/handle/45760611-7/6993]  
专题光学天文与技术应用研究室_光学天文技术研究团组
光学天文与技术应用研究室_利用南山1米大视场望远镜（NOWT）观测数据的文章
通讯作者Wang, Lei; Zhang, Xiaoming; Jiang, Xiaojun
作者单位1.Chinese Acad Sci, CAS Key Lab Opt Astron, Natl Astron Observ, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Changchun Observ, Natl Astron Observ, Changchun 130117, Peoples R China
3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Lei,Zhang, Xiaoming,Bai, Chunhai,et al. Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2024,534(1):385-399.
APA Wang, Lei.,Zhang, Xiaoming.,Bai, Chunhai.,Xie, Haiwen.,Li, Juan.,...&Jiang, Xiaojun.(2024).Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,534(1),385-399.
MLA Wang, Lei,et al."Rapid automatic multiple moving objects detection method based on feature extraction from images with non-sidereal tracking".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 534.1(2024):385-399.

入库方式： OAI收割

来源：新疆天文台

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