RFI Flagging in Solar and Space Weather Low Frequency Radio Observations

TL;DR

This paper explores advanced RFI detection methods for low frequency solar and space weather radio observations, addressing the challenge of distinguishing RFI from solar radio bursts to improve data quality.

Contribution

It introduces a novel RFI flagging technique using morphology convolution and a strategy for AOFlagger tailored for solar observations.

Findings

The methods effectively distinguish RFI from solar radio bursts.

The proposed algorithms improve data quality by accurately flagging RFI.

The morphology convolution approach preserves solar burst signals during flagging.

Abstract

Radio spectroscopy provides a unique inspection perspective for solar and space weather research, which can reveal the plasma and energetic electron information in the solar corona and inner heliosphere. However, Radio-Frequency Interference (RFI) from human activities affects sensitive radio telescopes, and significantly affects the quality of observation. Thus, RFI detection and mitigation for the observations is necessary to obtain high quality, science-ready data. The flagging of RFI is particularly challenging for the solar and space weather observations at low frequency, because the solar radio bursts can be brighter than the RFI, and may show similar temporal behavior. In this work, we investigate RFI flagging methods for solar and space weather observations, including a strategy for AOFlagger, and a novel method that makes use of a morphology convolution. These algorithms can effectively flag RFI while preserving solar radio bursts.