Extremely large ionospheric spatial gradients could cause potential integrity threats to the users of Global Navigation Satellite Systems (GNSS) augmentation systems. Thus these ionospheric anomalies need to be monitored by ground reference stations and the users must be alarmed within time-to-alerts. The ionospheric anomaly threat models are developing using data collected from GNSS reference stations. The use of poor-quality GNSS data degrades the accuracy of ionospheric delay estimates, and thus the performance of the resulting threat models. This paper presents a comprehensive method of GNSS data quality determination and evaluation, and provides data quality criteria to be used for ionospheric data analysis. These algorithms are tested using data collected from domestic reference stations. A series of data quality measurement algorithms provides quantitative measures on receiver cycle slips, multipath on code, receiver signal-to-noise ratios, receiver noise, and the daily number of observations. The results from the algorithms could be utilized to build global and local ionospheric anomaly threat models.

Keywords: GNSS augmentation systems, ionospheric anomaly, GNSS data quality check