J. Space Weather Space Clim.
Volume 8, 2018
|Number of page(s)||18|
|Published online||10 October 2018|
A method for the automated detection of solar radio bursts in dynamic spectra
PRISME, University of Orléans, EA4229, 8 rue Leonard de Vinci, 45072
2 LESIA-UMR 8109, Observatory de Paris, PSL Res. Univ., CNRS, Sorbonne Univ., Univ. Paris-Diderot, 5 place Jules Janssen, 92190 Meudon, France
3 Station de Radioastronomie de Nançay, Observatoire de Paris, PSL Res. Univ., CNRS, Univ. Orléans, OSUC, 18330 Nançay, France
* Corresponding author: firstname.lastname@example.org
Accepted: 26 July 2018
The variability of the solar corona, including flares and coronal mass ejections, affects the space environment of the Earth (heating and ionization of the atmosphere, magnetic field disturbances, and bombardment by high-energy particles). Electromagnetic emissions are the first signatures of a solar eruptive event which by modifying the electron density in the ionosphere may affect airborne technology and radio communications systems. In this paper, we present a new method to detect automatically radio bursts using data from the Nançay Decametre Array (NDA) in the band 10 MHz–80 MHz. This method starts with eliminating unwanted signals (Radio-Frequency Interference, RFI and Calibration signals) by analyzing the dynamic spectrum of the signal recorded in time. Then, a gradient median filter is applied to smooth and to reduce the variability of the signal. After denoising the signal, an automated solar radio burst detection system is applied. This system is based on a sequential procedure with adaptive constant-false-alarm rate (CFAR like detector) aimed to extract the spectra of major solar bursts. To this end, a semi-automatic software package is also developed to create a data base of all possible events (type II, III, IV or other) that could be detected and used for our performance assessment.
Key words: solar radio bursts / automatic detection / dynamic spectra / events type II, III and IV
© H. Salmane et al., Published by EDP Sciences 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.