@article {726, title = {Wide-field auroral imager onboard the Fengyun satellite}, journal = {Light: Science \& Applications}, volume = {8}, year = {2019}, month = {05/2019}, abstract = {

The newly launched Fengyun-3D (FY-3D) satellite carried a wide-field auroral imager (WAI) that was developed by Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CIOMP), which will provide a large field of view (FOV), high spatial resolution, and broadband ultraviolet images of the aurora and the ionosphere by imaging the N2 LBH bands of emissions. The WAI consists of two identical cameras, each with an FOV of 68{\textdegree} in the along-track direction and 10{\textdegree} in the cross-track direction. The two cameras are tilted relative to each other to cover a fan-shaped field of size 130{\textdegree} {\texttimes} 10{\textdegree}. Each camera consists of an unobstructed four-mirror anastigmatic optical system, a BaF2 filter, and a photon-counting imaging detector. The spatial resolution of WAI is ~10 km at the nadir point at a reference height of 110 km above the Earth{\textquoteright}s surface. The sensitivity is \>0.01 counts s-1 Rayleigh-1 pixel-1 (140{\textendash}180 nm) for both cameras, which is sufficient for mapping the boundaries and the fine structures of the auroral oval during storms/substorms. Based on the tests and calibrations that were conducted prior to launch, the data processing algorithm includes photon signal decoding, geometric distortion correction, photometric correction, flat-field correction, line-of-sight projection and correction, and normalization between the two cameras. Preliminarily processed images are compared with DMSP SSUSI images. The agreement between the images that were captured by two instruments demonstrates that the WAI and the data processing algorithm operate normally and can provide high-quality scientific data for future studies on auroral dynamics.

}, doi = {10.1038/s41377-019-0157-7}, url = {http://www.nature.com/articles/s41377-019-0157-7}, author = {Zhang, Xiao-Xin and Chen, Bo and He, Fei and Song, Ke-Fei and He, Ling-Ping and Liu, Shi-Jie and Guo, Quan-Feng and Li, Jia-Wei and Wang, Xiao-Dong and Zhang, Hong-Ji and Wang, Hai-Feng and Han, Zhen-Wei and Sun, Liang and Zhang, Pei-Jie and Dai, Shuang and Ding, Guang-Xing and Chen, Li-Heng and Wang, Zhong-Su and Shi, Guang-Wei and Zhang, Xin and Yu, Chao and Yang, Zhong-Dong and Zhang, Peng and Wang, Jin-Song} } @article {658, title = {A new auroral boundary determination algorithm based on observations from TIMED/GUVI and DMSP/SSUSI}, journal = {Journal of Geophysical Research: Space Physics}, volume = {122}, year = {2017}, month = {01/2017}, pages = {2162 - 2173}, abstract = {

An automatic auroral boundary determination algorithm is proposed in this study based on the partial auroral oval images from the Global Ultraviolet Imager (GUVI) aboard the Thermosphere{\textendash}Ionosphere-Mesosphere Energetics and Dynamics satellite and the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) aboard the Defense Meteorological Satellite Program (DMSP F16). This algorithm based on the fuzzy local information C-means clustering segmentation can be used to extract the auroral oval poleward and equatorward boundaries from merged images with filled gaps from both GUVI and SSUSI. Both extracted poleward and equatorward boundary locations are used to fit the global shape of the auroral oval with a off-center quasi-elliptical fitting technique. Comparison of the extracted auroral oval boundaries with those identified from the DMSP SSJ observations demonstrates that this new proposed algorithm can reliably be used to construct the global configuration of auroral ovals under different geomagnetic activities at different local times. The statistical errors of magnetic latitudes of the fitted auroral oval boundaries were generally less than 3{\textdegree} at 2 sigma and indicate that the the fitted boundaries agree better with b2e and b5e than b1e and b6 boundaries. This proposed algorithm provides us with a useful tool to extract the global shape and position of the auroral oval from the partial auroral images.

}, issn = {2169-9380}, doi = {10.1002/jgra.v122.210.1002/2016JA023295}, url = {https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2016JA023295}, author = {Ding, Guang-Xing and He, Fei and Zhang, Xiao-Xin and Chen, Bo} }