Monitoring and mitigation of ionospheric anomalies for GNSS-based safety-critical systems: towards ‘wheels on runway’ in all weather conditions at airports worldwide

Ionospheric anomaly threat models and mitigation techniques were developed via systematic and comprehensive analysis on the characteristics of ionospheric anomalies for each geomagnetic region. The developed techniques would enable worldwide Global Navigation Satellite System (GNSS)-based aircraft precision approach and landing in all weather and visibility conditions with a high level of navigation safety.

Article | Spring 2020

Global Navigation Satellite System (GNSS)-based aircraft precision approach and landing systems have been developed to get aircraft ‘wheels on runway’ in all weather and visibility conditions. The Ground-Based Augmentation System (GBAS) is one of the GNSS augmentation systems that currently support Category (CAT)-I operations at a number of airports worldwide. This service allows automatic precision approaches down to a decision height of 200 ft.

 

The ionosphere has been the most challenging source of error to be mitigated within the community of GBAS. While most of the ionospheric delays are removed after differential GNSS corrections are applied, residual ionospheric errors still can exist due to spatial decorrelation between the ground facility and users. In addition, GNSS signals can experience deep and frequent signal fading and random phase fluctuation, known as ionospheric scintillation, due to electron density irregularities, as illustrated in Figure 1.

A KAIST research team lead by Jiyun Lee, an associate professor of the Department of Aerospace Engineering, collaborated with international groups including Stanford University and the University of Colorado Boulder to develop ionospheric monitoring and mitigation techniques to support worldwide GBAS operations. In order to develop methods to detect and mitigate hazardously large ionospheric spatial gradients, the research team developed ionospheric anomaly threat models using GNSS observation data collected from a region where GBAS will be fielded. Figure 2 shows Equatorial Plasma Bubble (EPB) ionospheric models and availability simulation results, and Figure 3 shows the threat models developed in each region that have different upper bounds on the worst ionospheric gradient.

 

 

The research team also developed a new mitigation technique using a Monte Carlo simulation that randomizes ionospheric scenarios using randomly-generated parameter combinations within the threat model. This research was published in IEEE Signal Processing Magazine (J. Lee et al., IEEE SPM, 34(5), 2017) and Navigation (M. Yoon et al., Navigation, 66(3), 2019).