Automated Detection of Solar Radio Bursts Using a Statistical Method

Abstract

Radio bursts from the solar corona can provide clues to forecast space weather hazards. After recent technology advancements, regular monitoring of radio bursts has increased and large observational data sets are produced. Hence, manual identification and classification of them is a challenging task. In this paper, we describe an algorithm to automatically identify radio bursts from dynamic solar radio spectrograms using a novel statistical method. We used e-CALLISTO radio spectrometer data observed at Gauribidanur observatory near Bangalore in India during 2013 -2014. We have studied the classifier performance using the receiver operating characteristics. Further, we studied type III bursts observed in the year 2014 and found that 75% of the observed bursts were below 200 MHz. Our analysis shows that the positions of the flare sites which are associated with the type III bursts with upper frequency cut-off 200 MHz

Trends and characteristics of high-frequency type II bursts detected by CALLISTO spectrometers

“…Figure 3b and +25 • at the latitudes. In general, the analyzed high-frequency type II bursts are close to the disk center, similar to the previous study by Singh et al (2019) on the analysis of type III using the statistical method.…”

pyCallisto: A Python Library To Process The CALLISTO Spectrometer Data

“…Further this library will play a significant role in developing automatic classification algorithms of different types of solar radio bursts (e.g. see Singh et al 2019).…”

Intense L-Band Solar Radio Bursts Detection Based on GNSS Carrier-To-Noise Ratio Decrease over Multi-Satellite and Multi-Station

“…It is extremely important to keep this system free of interference. Types of interference with GNSS include multipath [ 3 , 4 ], ionospheric scintillation [ 5 ], spoofing [ 6 , 7 ], electromagnetic interference, satellite signal anomalies, and intense L-band solar radio bursts (SRBs) [ 8 ]. SRB is a strong signal in the microwave band from solar plasma radiation and cyclotron synchrotron radiation.…”

“…Zhang et al [ 25 , 26 ] designed an event recognition-analysis system that can automatically detect solar type III radio bursts and mine burst information from the dynamic spectra observed by the Nancay Decameter Array (NDA). Singh et al [ 8 ] proposed an automated method to detect SRBs. Although the method does not classify the types of radio bursts, it is able to discriminate between dynamic spectra with and without SRBs.…”