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A robust RFI identification for radio interferometry based on a convolutional neural network
Sun, Haomin1,2; Deng, Hui1,2; Wang, Feng1,2; Mei, Ying1,2; Xu, Tingting1,2; Smirnov, Oleg3; Deng LH(邓林华)4; Wei, Shoulin5
发表期刊MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
2022-03-24
卷号512期号:2页码:2025-2033
DOI10.1093/mnras/stac570
产权排序第4完成单位
收录类别SCI ; EI
关键词methods: data analysis techniques: interferometric
摘要

The rapid development of new generation radio interferometers such as the Square Kilometer Array (SKA) has opened up unprecedented opportunities for astronomical research. However, anthropogenic radio frequency interference (RFI) from communication technologies and other human activities severely affects the fidelity of observational data. It also significantly reduces the sensitivity of the telescopes. We proposed a robust convolutional neural network (CNN) model to identify RFI based on machine-learning methods. We overlaid RFI on the simulation data of SKA1-LOW to construct three visibility function data sets. One data set was used for modelling, and the other two were used for validating the model's usability. The experimental results show that the area under the curve reaches 0.93, with satisfactory accuracy and precision. We then further investigated the effectiveness of the model by identifying the RFI in the actual observational data from LOFAR and MeerKAT. The results show that the model performs well. The overall effectiveness is comparable to AOFlagger software and provides an improvement over existing methods in some instances.

资助项目National SKA Program of China[2020SKA0110300] ; Funds for International Cooperation and Exchange of the National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11961141001] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11903009] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[U1931141] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[U1831204] ; Innovation Research for the Postgraduates of Guangzhou University[2020GDJC-D20] ; Fundamental and Application Research Project of Guangzhou[202102020677] ; Astronomical Big Data Joint Research Center ; Chinese Academy of Sciences (CAS)Chinese Academy of Sciences[U1931141] ; Chinese Academy of Sciences (CAS)Chinese Academy of Sciences[U1831204]
项目资助者National SKA Program of China[2020SKA0110300] ; Funds for International Cooperation and Exchange of the National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11961141001] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11903009, U1931141, U1831204] ; Innovation Research for the Postgraduates of Guangzhou University[2020GDJC-D20] ; Fundamental and Application Research Project of Guangzhou[202102020677] ; Astronomical Big Data Joint Research Center ; Chinese Academy of Sciences (CAS)Chinese Academy of Sciences[U1931141, U1831204]
语种英语
学科领域天文学 ; 射电天文学 ; 射电天文方法 ; 射电天文学其他学科 ; 计算机科学技术 ; 计算机应用
学科门类理学 ; 理学::天文学 ; 工学 ; 工学::计算机科学与技术(可授工学、理学学位)
文章类型Article
出版者OXFORD UNIV PRESS
出版地GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
ISSN0035-8711
URL查看原文
WOS记录号WOS:000773022100014
WOS研究方向Astronomy & Astrophysics
WOS类目Astronomy & Astrophysics
关键词[WOS]FREQUENCY INTERFERENCE MITIGATION ; REIONIZATION
EI入藏号20221712011962
EI主题词Radio interference
EI分类号716.1 Information Theory and Signal Processing - 716.3 Radio Systems and Equipment - 941.3 Optical Instruments - 941.4 Optical Variables Measurements
引用统计
被引频次:11[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
版本出版稿
条目标识符http://ir.ynao.ac.cn/handle/114a53/25001
专题抚仙湖太阳观测和研究基地
通讯作者Deng, Hui; Wang, Feng
作者单位1.Center For Astrophysics, Guangzhou University, Guangzhou 510006, PR China;
2.Great Bay Center, National Astronomical Data Center, Guangzhou, Guangdong 510006, PR China;
3.Department of Physics and Electronics, Rhodes University, PO Box 94, Makhanda 6140, South Africa;
4.Yunnan Observatory, Chinese Academy of Sciences, Kunming, Yunnan, 650216, PR China;
5.Key Lab Of Computer Technology Appliance, Kunming University of Science And Technology, Kunming, Yunnan 650500, PR China
推荐引用方式
GB/T 7714
Sun, Haomin,Deng, Hui,Wang, Feng,et al. A robust RFI identification for radio interferometry based on a convolutional neural network[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2022,512(2):2025-2033.
APA Sun, Haomin.,Deng, Hui.,Wang, Feng.,Mei, Ying.,Xu, Tingting.,...&Wei, Shoulin.(2022).A robust RFI identification for radio interferometry based on a convolutional neural network.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,512(2),2025-2033.
MLA Sun, Haomin,et al."A robust RFI identification for radio interferometry based on a convolutional neural network".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 512.2(2022):2025-2033.
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