YNAO OpenIR  > 天文技术实验室
Detection and mitigation of RFI in SBRS observation data
Qiang, Zhen-Ping1,2; Cheng, Jun2; Shang, Zhen-Hong3; Ji KF(季凯帆)4; Dai, Fei1; Liu H(刘辉)4
发表期刊RESEARCH IN ASTRONOMY AND ASTROPHYSICS
2021-10
卷号21期号:8
DOI10.1088/1674-4527/21/8/195
产权排序第4完成单位
收录类别SCI
关键词spectrographs: SBRS techniques: image processing and spectroscopic Sun : radio radiation
摘要

In view of the inconsistency of channel gains and a large amount of interference noise in Solar Broadband Radio Spectrometer (SBRS) observation data, they will seriously affect the analysis of SBRS data. In this paper, a method of Radio Frequency Interference (RFI) detection and mitigation for SBRS observation data is reported. Firstly, the SBRS observation data are preprocessed, a part of the observation data was selected to calculate the mean and variance to achieve the normalization of the entire observation data, which can avoid the influence of strong noise on the normalization result. Furthermore, we proposed an adaptive threshold RFI detection method based on fusion wavelet transform reconstruction and an RFI elimination method based on neighborhood weighted filling. It is worth mentioning that to detect RFI interference signals of different magnitudes, we adopted an iterative approach to the RFI detection and mitigation process. Through qualitative analysis of real observation data and quantitative analysis of simulated data, it is shown that the method proposed in this paper can effectively eliminate RFI in SBRS observation data, and improve the quality of observation data for further scientific analysis.

资助项目Open Research Program of CAS Key Laboratory of Solar Activity, National Astronomical Observatories[KLSA201909] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11773072] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11873027] ; Yunnan Fundamental Research Projects[202001AT070135]
项目资助者Open Research Program of CAS Key Laboratory of Solar Activity, National Astronomical Observatories[KLSA201909] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC)[11773072, 11873027] ; Yunnan Fundamental Research Projects[202001AT070135]
语种英语
学科领域天文学 ; 太阳与太阳系 ; 计算机科学技术 ; 计算机应用
文章类型Article
出版者NATL ASTRONOMICAL OBSERVATORIES, CHIN ACAD SCIENCES
出版地20A DATUN RD, CHAOYANG, BEIJING, 100012, PEOPLES R CHINA
ISSN1674-4527
URL查看原文
WOS记录号WOS:000711653400001
WOS研究方向Astronomy & Astrophysics
WOS类目Astronomy & Astrophysics
关键词[WOS]PULSATING STRUCTURE ; SOLAR ; FLARE
引用统计
被引频次:2[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/114a53/24642
专题天文技术实验室
通讯作者Liu H(刘辉)
作者单位1.College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China;
2.CAS Key Laboratory of Solar Activity, National Astronomical Observatories, Beijing 100101, China;
3.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China;
4.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, China
通讯作者单位中国科学院云南天文台
推荐引用方式
GB/T 7714
Qiang, Zhen-Ping,Cheng, Jun,Shang, Zhen-Hong,et al. Detection and mitigation of RFI in SBRS observation data[J]. RESEARCH IN ASTRONOMY AND ASTROPHYSICS,2021,21(8).
APA Qiang, Zhen-Ping,Cheng, Jun,Shang, Zhen-Hong,Ji KF,Dai, Fei,&Liu H.(2021).Detection and mitigation of RFI in SBRS observation data.RESEARCH IN ASTRONOMY AND ASTROPHYSICS,21(8).
MLA Qiang, Zhen-Ping,et al."Detection and mitigation of RFI in SBRS observation data".RESEARCH IN ASTRONOMY AND ASTROPHYSICS 21.8(2021).
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Detection and mitiga(3017KB)期刊论文出版稿开放获取CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Qiang, Zhen-Ping]的文章
[Cheng, Jun]的文章
[Shang, Zhen-Hong]的文章
百度学术
百度学术中相似的文章
[Qiang, Zhen-Ping]的文章
[Cheng, Jun]的文章
[Shang, Zhen-Hong]的文章
必应学术
必应学术中相似的文章
[Qiang, Zhen-Ping]的文章
[Cheng, Jun]的文章
[Shang, Zhen-Hong]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Detection and mitigation of RFI in SBRS observation data.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。