Data Quality Improvements and Applications of Long-Term Monitoring of Ionospheric Anomalies for GBAS

Minchan Kim, Jiyun Lee, Sam Pullen, Joseph Gillespie

Abstract:	The Long-Term Ionospheric Anomaly Monitoring (LTIAM) tool is an automated software package designed to analyze past data and support continuous ionospheric monitoring of both nominal and anomalous ionospheric spatial gradients. While automated measurement screening is included, large gradients observed by LTIAM require manual validation to confirm that they were caused by the ionosphere instead of faulty measurements or data recording. Ground stations with poor data quality thus add greatly to the burden of LTIAM processing. This paper develops an automated approach to data quality measurement for CORS and IGS ground stations. This method is used to identify stations that are poor according to multiple quality metrics. Thresholds are established for each quality metric, and stations violating one or more thresholds are removed from use by LTIAM unless their geographical position is sufficiently important. Use of this method with CORS stations in the Conterminous U.S. (CONUS) eliminates the almost 90% of spurious or false gradients while only excluding 16% of the over 1500 CORS stations in CONUS. This paper also investigates past CONUS ionospheric storm data to understand the distribution of anomalous spatial gradients. Examining LTIAM outputs on known storm days with gradients between 50 and 200 mm/km demonstrates that these smaller (but still anomalous) gradients are far more likely than extreme gradients above 200 mm/km. The continued use of LTIAM over the next solar peak should help us refine our knowledge of this distribution as well as the overall likelihood of large spatial gradients under anomalous ionospheric conditions.
Published in:	Proceedings of the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2012) September 17 - 21, 2012 Nashville Convention Center, Nashville, Tennessee Nashville, TN
Pages:	2159 - 2174
Cite this article:	Kim, Minchan, Lee, Jiyun, Pullen, Sam, Gillespie, Joseph, "Data Quality Improvements and Applications of Long-Term Monitoring of Ionospheric Anomalies for GBAS," Proceedings of the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2012), Nashville, TN, September 2012, pp. 2159-2174.
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