• Journal of Astronomy and Space Sciences
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• 제21권4호
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• pp.441-452
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• 2004

실시간 관측자료를 사용하여 현재상태를 진단하고 이후의 변화를 예보하는 것은 우주환경 모니터링 시스템의 필수적인 요소라 할 수 있다. 본 연구에서는 ION(IDL On the Net)을 이용하여 웹 기반의 우주환경모니터링 시스템을 구축하였다(http://sun.kao.re.kr). 이 웹 페이지에서는 현재의 태양 및 지자기 데이터를 보여주고 위성, 통신, 지상 전력시스템에 줄 수 있는 영향을 예측하여 제시하고 있다. 그리고 NOAA/SEC에서 매일 제시하는 태양 X선 플레어, 프로톤 현상, 지자기 폭풍의 예보결과를 표시한다. 또한 행성간 태양 충격파와 CME(Coronal Mass Ejection; 코로나 물질 방출)의 지구도달 시간을 예측하기 위해 두 가지의 예측모델이 웹에서 구동되도록 하였다. 현재 우리는 여러가지 태양 및 지자기 활동과 관련된 각종데이터를 IDL과 FTP 프로그램을 사용하여 실시간으로 다운받아 우주환경 데이터베이스를 확장하고 있다. 본 논문에서는 한국천문연구원의 우주환경모니터링시스템 개발에 관하여 자세히 기술한다.

• Journal of Astronomy and Space Sciences
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• 제21권4호
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• pp.329-342
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• 2004

In this paper, we present preliminary feasibility studies on three types of solar observation payloads for future Korean Science and Technology Satellite (STSAT) programs. The three candidates are (1) an UV imaging telescope, (2) an UV spectrograph, and (3) an X-ray spectrometer. In the case of UV imaging telescope, the most important constraint seems to be the control stability of a satellite in order to obtain a reasonably good spatial resolution. Considering that the current pointing stability estimated from the data of the Far ultraviolet Imaging Spectrograph (FIMS) onboard the Korean STSAT-1, is around 1 arc minutes/sec, we think that it is hard to obtain a spatial resolution sufficient for scientific research by such an UV Imaging Telescope. For solar imaging missions, we realize that an image stabilization system, which is composed of a small guide telescope with limb sensor and a servo controller of secondary mirror, is quite essential for a very good pointing stability of about 0.1 arcsec. An UV spectrograph covering the solar full disk seems to be a good choice in that there is no risk due to poor pointing stability as well as that it can provide us with valuable UV spectral irradiance data valuable for studying their effects on the Earth's atmosphere and satellites. The heritage of the FIMS can be a great advantage of developing the UV spectrograph. Its main disadvantage is that two major missions are in operation or scheduled. Our preliminary investigations show that an X-ray spectrometer for the full disk Sun seems to be the best choice among the three candidates. The reasons are : (1) high temporal and spectral X-ray data are very essential for studying the acceleration process of energetic particles associated with solar flares, (2) we have a good heritage of X-ray detectors including a rocket-borne X-ray detector, (3) in the case of developing countries such as India and Czech, solar X-ray spectrometers were selected as their early stage satellite missions due to their poor pointing stabilities, and (4) there is no planned major mission after currently operating Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) mission. Finally, we present a preliminary design of a solar X-ray spectrometer covering soft X-ray (2 keV) to gamma ray (10 MeV).

• 천문학회지
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• 제56권2호
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.