标题：Markov Chain-Based Stochastic Modeling of Deep Signal Fading: Availability Assessment of Dual-Frequency GNSS-Based Aviation Under Ionospheric Scintillation
摘要：Deep signal fading due to ionospheric scintillation severely impacts global navigation satellite system (GNSS)-based applications. GNSS receivers run the risk of signal loss under deep fading, which directly leads to a significant decrease in navigation availability. The impact of scintillation on GNSS-based applications can be mitigated via dual-frequency signals which provide a backup channel. However, the benefit of dual-frequency diversity highly depends on the correlation of fading processes between signals at different frequencies. This paper proposes a Markov chain-based model that simulates the actual behavior of correlated fading processes in dual-frequency channels. A set of recorded scintillation data was used to capture transitions among all fading states based on the fading and recovery of each signal frequency. A statistical study of deep fading characteristics in this data revealed that the Markov chain-based model accurately generates realistic correlated fading processes. Using the proposed model, aviation availability of localizer performance with vertical guidance down to a 200-foot decision height (“LPV-200”) under a strong scintillation scenario is analyzed by considering the effects of signal outages due to deep fading. A parametric analysis of the availability resulting from variations in mean time to loss of lock, mean time to reacquisition, and ionospheric delay uncertainty was conducted to investigate the performance standards on GNSS-based aviation under scintillation. The analysis results demonstrate a significant benefit of frequency diversity on aviation availability during scintillation. This model will further enable the assessment of GNSS-based availability for aviation and other applications under a full range of scintillation conditions.
