Detection and mitigation of RFI in SBRS observation data

作     者：Zhen-Ping Qiang Jun Cheng Zhen-Hong Shang Kai-Fan Ji Fei Dai Hui Liu Zhen-Ping Qiang;Jun Cheng;Zhen-Hong Shang;Kai-Fan Ji;Fei Dai;Hui Liu

作者机构：College of Big Data and Intelligent EngineeringSouthwest Forestry UniversityKunming 650224China CAS Key Laboratory of Solar ActivityNational Astronomical ObservatoriesBeijing 100101China Faculty of Information Engineering and AutomationKunming University of Science and TechnologyKunming 650504China Yunnan ObservatoriesChinese Academy of SciencesKunming 650216China 

出 版 物：《Research in Astronomy and Astrophysics》 (天文和天体物理学研究（英文版）)

年 卷 期：2021年第21卷第8期

页      面：111-123页

核心收录：

学科分类：07[理学] 070401[理学-天体物理] 0704[理学-天文学] 

基　　金：funded by the Open Research Program of CAS Key Laboratory of Solar Activity,National Astronomical Observatories (KLSA201909) the National Natural Science Foundation of China (Nos.11773072 and 11873027) Yunnan Fundamental Research Projects (202001AT070135) 

主　　题：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 *** this paper,a method of Radio Frequency Interference(RFI) detection and mitigation for SBRS observation data is ***,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 ***,we proposed an adaptive threshold RFI detection method based on fusion wavelet transform reconstruction and an RFI elimination method based on neighborhood weighted *** is worth mentioning that to detect RFI interference signals of different magnitudes,we adopted an iterative approach to the RFI detection and mitigation *** 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.