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 propo...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.展开更多
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)+1 种基金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 Programthe Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB23000000)。
文摘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.
