论文标题
GWAC系统中的流星候选者选择的算法
An algorithm of selection of meteor candidates in GWAC system
论文作者
论文摘要
GWAC凭借其众多的视野，每天可以记录数百个流星。这些流星对于某些流星研究小组来说是宝贵的宝藏。因此，准确找到所有这些流星非常重要。为了应对像GWAC一样的天空调查系统中精确区分流星和其他细长物体的挑战，我们设计和实施流星候选识别算法，包括对流星候选者光曲线的识别和形态分析。尽管该算法可能会过滤一些真实的流星，但它可以高度置信度提供流星样本。在处理了两个月内拍摄的迷你GWAC图像后，我们检测到109,000个细长的物体，其中超过90％的物体不是流星。在细长的对象中，根据单个帧中的存在，光曲线中的单个峰和光曲线的缓慢变化，将约5.9％的对象识别为具有高置信度的流星。
With its large field of view, GWAC can record hundreds of meteors every day. These meteors are valuable treasures for some meteor research groups. It is therefore very important to accurately find all of these meteors. To address the challenge of precisely distinguishing meteors from other elongated objects in a GWAC-like sky survey system, we design and implement a meteor candidate recognition algorithm, including the recognizing and morphology analysis of the light curves of the meteor candidates. Although the algorithm may filter out some real meteors, it can provide a sample of meteor with high confidence. After processing the images of Mini-GWAC taken in two months, we detect 109,000 elongated objects in which more than 90 percent of objects are not meteor. Among the elongated objects, about 5.9% objects are identified as meteors with high confidence, after the filters based upon an existence in a single frame, a single peak in the light curves, and a slow variation of the light curves.
