Optimized GNSS Network Station Selection to Support the Development of Ionospheric Threat Models for GBAS

Minchan Kim, Jiyun Lee, Sam Pullen, Joseph Gillespie

Abstract:	Extremely large ionospheric spatial gradients present 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 users must be alarmed within time-to-alerts. The long-term ionospheric anomaly monitoring (LTIAM) tool has been developed to monitor ionospheric behavior continuously over the life cycle of ground-based augmentation systems (GBAS) and to build ionosphere threat models for all regions where GBAS will be fielded in the future. However, the use of poor-quality GNSS data degrades the accuracy of ionospheric delay estimates, produces many faulty anomaly candidates and thus adds a great burden to LTIAM processing. This paper develops a methodology to select a set of welldistributed, high-quality stations from GNSS reference station networks. An optimized set of thresholds for data quality metrics, which maximize the elimination of spurious gradients while minimizing unnecessary station removals, are established by the high-quality station selection method. This method performs better that the previously developed method which determine thresholds independently for each quality metric without considering the interrelations between other quality metrics. The welldistributed sub-network selection method is also proposed to remove geographically redundant stations in dense regions. The number of CORS stations in the Conterminous U.S. (CONUS) is reduced to 46% of the total stations when a desired baseline constraint is 100 km. This paper also verifies the performance of the proposed method by processing data collected from other GNSS reference station networks.
Published in:	Proceedings of the 2013 International Technical Meeting of The Institute of Navigation January 29 - 27, 2013 Catamaran Resort Hotel San Diego, California
Pages:	559 - 570
Cite this article:	Kim, Minchan, Lee, Jiyun, Pullen, Sam, Gillespie, Joseph, "Optimized GNSS Network Station Selection to Support the Development of Ionospheric Threat Models for GBAS," Proceedings of the 2013 International Technical Meeting of The Institute of Navigation, San Diego, California, January 2013, pp. 559-570.
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