Kim Minchan, Seo Jiwon, Lee Jiyun
Division of Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 305-701, Korea.
School of Integrated Technology, Yonsei University, 85 Songdogwahak-ro, Incheon 406-840, Korea.
Sensors (Basel). 2014 Aug 14;14(8):14971-93. doi: 10.3390/s140814971.
Global Navigation Satellite Systems (GNSS) are now recognized as cost-effective tools for ionospheric studies by providing the global coverage through worldwide networks of GNSS stations. While GNSS networks continue to expand to improve the observability of the ionosphere, the amount of poor quality GNSS observation data is also increasing and the use of poor-quality GNSS data degrades the accuracy of ionospheric measurements. This paper develops a comprehensive method to determine the quality of GNSS observations for the purpose of ionospheric studies. The algorithms are designed especially to compute key GNSS data quality parameters which affect the quality of ionospheric product. The quality of data collected from the Continuously Operating Reference Stations (CORS) network in the conterminous United States (CONUS) is analyzed. The resulting quality varies widely, depending on each station and the data quality of individual stations persists for an extended time period. When compared to conventional methods, the quality parameters obtained from the proposed method have a stronger correlation with the quality of ionospheric data. The results suggest that a set of data quality parameters when used in combination can effectively select stations with high-quality GNSS data and improve the performance of ionospheric data analysis.
全球导航卫星系统（GNSS）如今被视为电离层研究中具有成本效益的工具，因为它通过全球范围内的GNSS站网络提供全球覆盖。虽然GNSS网络不断扩展以提高对电离层的观测能力，但质量较差的GNSS观测数据量也在增加，而使用质量不佳的GNSS数据会降低电离层测量的精度。本文开发了一种综合方法来确定用于电离层研究的GNSS观测质量。这些算法专门设计用于计算影响电离层产品质量的关键GNSS数据质量参数。对从美国本土（CONUS）的连续运行参考站（CORS）网络收集的数据质量进行了分析。结果质量差异很大，这取决于每个站点，并且各个站点的数据质量在较长时间段内持续存在。与传统方法相比，从所提出的方法获得的质量参数与电离层数据质量具有更强的相关性。结果表明，一组数据质量参数结合使用时可以有效地选择具有高质量GNSS数据的站点，并提高电离层数据分析的性能。
