Reliability monitoring of GNSS observables under the influence of ionospheric disturbances

• Published in: 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS) pp. 431 - 441
• Main Authors: Wezka, Kinga, Herrera-Pinzon, Ivan, Galas, Roman
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01-04-2016
• Subjects: Accuracy; Algorithms; GNSS; Indexes; Ionospheric disturbances; ionospheric scintillation; Mathematical model; Mathematical models; Monitoring; Position (location); RAIM; Receivers; Reliability; Satellites; Scintillation; Stochastic processes; Stochasticity
• ISSN: 2153-3598
• DOI: 10.1109/PLANS.2016.7479731

In recent years GNSS has become the recognised core element for the provision of accurate and reliable positioning, velocity and timing (PVT) data for multiple navigational applications. However, since the occurrence of strong ionospheric disturbances impacts the accuracy of GNSS measurements leading consequently to unreliable PVT solutions, not only precision and accuracy but also high-level reliability on the GNSS based solutions is demanded. For autonomously working GNSS receivers, it is necessary to provide algorithms responsible for the reliability control, with the ability to mitigate the influence of such phenomena. Traditionally, geometrical parameters, such as the elevation angle, and signal-related parameters, such as the C/N0, are used to describe the quality properties of GNSS observables. Nevertheless, parameters derived from physical phenomena, such as ionospheric scintillations, can provide additional information not correlated with these aforementioned approaches. The use of indices describing ionospheric scintillations is expected to provide the opportunity of improved error detection for the mitigation of threats. Thus, this work proposes the assessment of the performance of a RAIM-based reliability algorithm using a stochastic model derived from scintillation indices, for the improvement of reliability and accuracy on the final positioning solutions, in comparison with the traditional elevation angle- and C/N0 based stochastic models. Initial results indicate the potential of this approach for GNSS applications under the influence of strong ionospheric disturbances and suggest the advantages of their use.