Radio frequency interference mitigation using pseudoinverse learning autoencoders  

作　　者：Hong-Feng Wang Mao Yuan Qian Yin Ping Guo Wei-Wei Zhu Di Li Si-Bo Feng 

机构地区：[1]Image Processing and Pattern Recognition Laboratory,School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China [2]CAS Key Laboratory of FAST,National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100101,China [3]School of Information Management,Dezhou University,Dezhou 253023,China [4]Image Processing and Pattern Recognition Laboratory,School of System Science,Beijing Normal University,Beijing 100875,China [5]Institute for Astronomical Science,Dezhou University,Dezhou 253023,China [6]University of Chinese Academy of Sciences,Beijing 100049,China [7]Hanvon Technology Co.,Ltd,Beijing 100193,China [8]NAOC-UKZN Computational Astrophysics Centre,University of KwaZulu-Natal,Durban 4000,South Africa

出　　处：《Research in Astronomy and Astrophysics》2020年第8期121-128,共8页天文和天体物理学研究（英文版）

基　　金：the National Natural Science Foundation of China(NSFC,Grant Nos.11988101,61472043,11743002,11873067,11690024,11673005 and 11725313);the Outstanding Youth Fund Project of Natural Science Fund of Shandong Province(Grant No.ZR2019YQ03);supported by the Joint Research Fund in Astronomy(U1531242)under cooperative agreement between the NSFC and the Chinese Academy of Sciences(CAS)supported by the Chinese Academy of Science Pioneer Hundred Talents Program;the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB23000000)。

摘　　要：Radio frequency interference(RFI)is an important challenge in radio astronomy.RFI comes from various sources and increasingly impacts astronomical observation as telescopes become more sensitive.In this study,we propose a fast and effective method for removing RFI in pulsar data.We use pseudo-inverse learning to train a single hidden layer auto-encoder(AE).We demonstrate that the AE can quickly learn the RFI signatures and then remove them from fast-sampled spectra,leaving real pulsar signals.This method has the advantage over traditional threshold-based filter method in that it does not completely remove contaminated channels,which could also contain useful astronomical information.

关 键 词：pulsars:general methods:numerical methods:data analysis 

分 类 号：P161[天文地球—天文学]