Automated Solar Flare Detection and Feature Extraction in High-Resolution and Full-Disk H$\upalpha$ Images

Yang, Meng; Tian, Yu; Liu, Yangyi; Rao, Changhui

doi:10.1007/s11207-018-1300-y

Cited by 5 publications

(1 citation statement)

References 21 publications

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“…Solar Demon (Kraaikamp and Verbeeck, 2015) uses SDO/AIA images to detect flares, dimming and EUV waves by tracking increase/decrease in intensity in regions that are identified by thresholds. Yang et al (2018) and Pötzi, Veronig, and Temmer (2018) also use similar region-based methods on H α images for real-time flare detection. The RHESSI Flare finder (Lin 2003) searches for microflares as local maxima in the 6 -12 keV count-rate timelines.…”

Section: Introductionmentioning

confidence: 99%

The Solar Ultra-Violet Imaging Telescope: On-board intelligence for flare observations

Varma

Padinhatteri

Sinha

et al. 2022

Preprint

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Aditya-L1 is India’s first observatory class Solar space mission to study the Sun from Lagrangian 1 position. The Solar Ultra-Violet Imaging Telescope (SUIT) is one of the payloads on-board Aditya-L1. SUIT is an off-axis Ritchey-Chretien (RC) telescope, which images the Sun on to a 4k x 4k CCD covering a field-of-view of 1.5Ro with a plate scale of 0.7'/pixel. One of the primary objectives of SUIT is to study the early evolution of solar flares with high time cadence in Near UV wavelength (200 nm – 400 nm). The SUIT on-board intelligence is developed to achieve this objective. The complete intelligence algorithm is divided into several sub-modules each working on a specific aspect of intelligence. These are, HEL1OS flare trigger module: generates flare trigger using HEL1OS hard X-ray data, flare localization module: locates flare on the SUIT full-disc images, Region of Interest (RoI) tracking module: accounts for shift in RoI coordinates caused due to rotation of the Sun, auto-exposure control module: adjusts the exposure time depending upon the flare intensity for better contrast. In this paper, these on-board intelligence modules are explained in detail. The working principles of these modules are tested using available data from various existing missions and also using synthesized data and the obtained results are presented. The modules are implemented in hardware using Actel RTAX 2000S FPGA and are tested using laboratory setup. From the testing, it is found that, flares are successfully localized in a mean time of 40 seconds from the GOES soft X-ray catalog start time. Also, a time cadence of under 3 seconds for a single filter flare RoI images is achieved.

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Section: Introductionmentioning

confidence: 99%