Modeling and Performance Analysis of Ionospheric Anomaly Front Velocity for GBAS

Cong Du, Kun Fang, Zhiqiang Dan, Qiang Li, Zhipeng Wang, Yanbo Zhu

Abstract:	Ionospheric anomaly can cause integrity threats to ground-based augmentation system (GBAS) users. In order to describe the physical characteristics of the ionosphere, an ionospheric threat model is proposed which consists of three important parameters, i.e., gradient, front velocity and front width. Although the gradient has been studied in previous works, the front velocity over China has not been fully analyzed. Therefore, this paper focuses on modeling the ionospheric anomaly front velocity based on the real data collected in China during an eleven-year period from 2008 to 2018. The performance of the developed model is analyzed. We present a method to restrict the distribution of available stations to improve the accuracy of the front velocity estimation. Then, as an example, the front velocity is estimated by stations in Yunnan Province on April 6, 2011. Statistical analysis is carried out to establish the new ionospheric threat model. Additionally, the aircraft approaching process under ionospheric anomaly is simulated. The simulation is repeated with all parameters varied in the ionospheric threat model. In this way, we explore the effects of different ionospheric anomalies on GBAS performance. Results show that the new model parameters of our methodology can reflect the characteristics of the ionospheric anomaly in China and produce no substantial differences in the estimation error for GBAS.
Published in:	Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021) September 20 - 24, 2021 Union Station Hotel St. Louis, Missouri
Pages:	1550 - 1564
Cite this article:	Du, Cong, Fang, Kun, Dan, Zhiqiang, Li, Qiang, Wang, Zhipeng, Zhu, Yanbo, "Modeling and Performance Analysis of Ionospheric Anomaly Front Velocity for GBAS," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 1550-1564. https://doi.org/10.33012/2021.17876
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