Automated solar radio burst detection on radio spectrum: a review of techniques in image processing

The information of solar atmosphere was obtained after investigating the recording radiation of the space mission. With technology growing recently, a lot of solar radio receiver was introduced to monitor the solar radio activity on the ground with high efficiency. It is recorded in every second for 24 hours per day. A massive of solar radio spectra data produced every day that makes it impossible to identify, whether the data contain burst or not. By doing manual detection, human effort and error become the issues when the solar astronomer needs the fast and accurate result. Recently, the success of various techniques in image processing to identify solar radio burst automatically was presented. This paper reviews previous technique in image processing. This discussion will help the solar astronomer to find the best technique in pre-processing before moving into the next stage for detection of solar radio burst.Keywords: monitoring solar activity; automated solar radio burst detection; image processing; techniqu

A method for the automated detection of solar radio bursts in dynamic spectra

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

Detección de anomalías mediante redes neuronales convolucionales (CNN) en radio espectrómetros solares

En este Trabajo Fin de Grado se va a desarrollar una red neuronal profunda, basada en capas convolucionales, cuyo objetivo será detectar anomalías en radio espectrómetros solares. Actualmente, esta tarea es realizada por una persona que analiza manualmente los espectros de radio. Sin embargo, gracias al avance de la ciencia en el campo de la inteligencia artificial, se espera que sea posible automatizar este trabajo mediante el uso de una red neuronal. Para ello, se utilizarán los datos recopilados por la Red Científica Internacional e-Callisto.In this Final Degree Project we are going to develop a deep neural network, based on convolutional layers, whose objective will be to detect anomalies in solar radio spectrometers. Currently, this task is done manually by a person who analyzes all data. However, thanks to the advancement of science in the field of artificial intelligence, it is expected that it will be possible to automate this work by using a neural network. For this purpose, we will use the data collected by the International Scientific Network e-Callisto.Grado en Ingeniería Informátic

An automated solar radio burst detection method in dynamic spectra images

International audienc

A method for the automated detection of solar radio bursts in dynamic spectra

International audienceThe 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