Institutional Repository of Radio Astronomy Research Laboratory
Parameterized reconstruction with random scales for radio synthesis imaging | |
Zhang, L.1; Mi, L. G.1; Zhang, M.2,3![]() ![]() | |
2021-02-04 | |
Source Publication | ASTRONOMY & ASTROPHYSICS
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ISSN | 0004-6361 |
Volume | 646Pages:A44 |
Contribution Rank | 2 |
Abstract | Context. In radio interferometry, incomplete sampling results in a dirty beam with side lobes, which obscures the celestial structures. Before the astrophysical analysis, the effects of the dirty beam need to be eliminated, which can be solved with various deconvolution methods.Aims. Diffuse astronomical sources observed by modern high-sensitivity telescopes tend to be complex morphological structures, often accompanied by faint features, which are submerged under the side lobes of the dirty beam. We propose a new deconvolution algorithm called random multiscale estimator (RMS-Clean), which is mainly used to solve the difficult reconstruction of diffuse astronomical sources.Methods. RMS-Clean models the sky brightness distribution as a linear combination of random multiscale basis functions whose scales are obtained by randomly perturbing a preset multiscale list. Random multiscale models are used to approximate the uncertain characteristics of the scales of complex astronomical sources.Results. When the RMS-Clean method is applied to simulations of SKA observations with realistic diffuse structures, it can reconstruct diffuse structures well and provides a competitive result compared to the commonly used deconvolution algorithms. |
Keyword | methods: data analysis techniques: image processing |
DOI | 10.1051/0004-6361/202039275 |
URL | 查看原文 |
Indexed By | SCI |
Language | 英语 |
WOS Keyword | DECONVOLUTION ; ALGORITHM |
Funding Project | National Natural Science Foundation of China[11963003] ; National Natural Science Foundation of China[61572461] ; National Natural Science Foundation of China[11790305] ; National Natural Science Foundation of China[U1831204] ; National SKA Program of China[2020SKA0110300] ; National Key R&D Program of China[2018YFA0404602] ; National Key R&D Program of China[2018YFA0404603] ; Guizhou Science & Technology Plan Project[[2017]5788] ; Youth Science & Technology Talents Development Project of Guizhou Education Department[[2018]119] ; Youth Science & Technology Talents Development Project of Guizhou Education Department[[2018]433]] ; Guizhou University Talent Research Fund[(2018)60] ; Guizhou University Talent Research Fund[2017-XBQNXZ-A-008] |
WOS Research Area | Astronomy & Astrophysics |
WOS Subject | Astronomy & Astrophysics |
WOS ID | WOS:000617329400001 |
Publisher | EDP SCIENCES S A |
Funding Organization | National Natural Science Foundation of China ; National SKA Program of China ; National Key R&D Program of China ; Guizhou Science & Technology Plan Project ; Youth Science & Technology Talents Development Project of Guizhou Education Department ; Guizhou University Talent Research Fund |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.xao.ac.cn/handle/45760611-7/3944 |
Collection | 射电天文研究室_星系宇宙学研究团组 |
Corresponding Author | Zhang, L. |
Affiliation | 1.Guizhou Univ, Coll Big Data & Informat Engn, Guiyang 550025, Peoples R China 2.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 3.Chinese Acad Sci, Key Lab Radio Astron, Urumqi 830011, Peoples R China 4.Chinese Acad Sci, Natl Astron Observ, Key Lab Solar Act, Beijing 100101, Peoples R China 5.Guangzhou Univ, Ctr Astrophys, Guangzhou 510006, Peoples R China |
Recommended Citation GB/T 7714 | Zhang, L.,Mi, L. G.,Zhang, M.,et al. Parameterized reconstruction with random scales for radio synthesis imaging[J]. ASTRONOMY & ASTROPHYSICS,2021,646:A44. |
APA | Zhang, L..,Mi, L. G..,Zhang, M..,Liu, X..,Xu, L..,...&Li, D. Y..(2021).Parameterized reconstruction with random scales for radio synthesis imaging.ASTRONOMY & ASTROPHYSICS,646,A44. |
MLA | Zhang, L.,et al."Parameterized reconstruction with random scales for radio synthesis imaging".ASTRONOMY & ASTROPHYSICS 646(2021):A44. |
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Zhang-2021-Parameter(11821KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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