ROTI‐Based Stochastic Model to Improve GNSS Precise Point Positioning Under Severe Geomagnetic Storm Activity. Issue 7 (1st July 2022) - Luo, Xiaomin; Du, Junfeng; Galera Monico, João Francisco; Xiong, Chao; Liu, Jingbin; Liang, Xinmei
Abstract: For global navigation satellite system (GNSS), ionospheric disturbances caused by the geomagnetic storm can reduce the accuracy and reliability of precision point positioning (PPP). At present, common stochastic models in GNSS PPP, such as the elevation angle stochastic (EAS) model or carrier‐to‐noise power‐density ratio ( C / N 0 $C/N_{0}$ ) based SIGMA‐ ε $ε $ model, do not properly consider storm effects on GNSS measurements. To mitigate severe storm effects on GNSS PPP, this study further implements the rate of total electron content index (ROTI) parameter into the EAS model referred to as the EAS‐ROTI model. This model contains two operations. The first one is to adjust variance of GNSS measurements using ROTI observations on EAS model. The second one is to determine the ratio of the priori variance factor between pseudorange and carrier phase measurements during severe storm conditions. The performance of EAS‐ROTI model is verified by using a large number of international GNSS service stations datasets on 17 March and 23 June in 2015. Experimental results indicate that on a global scale, the EAS‐ROTI model improves the PPP accuracy in 3D direction by approximately 12.9%–14.7% compared with the EAS model, and by about 24.8%–45.9% compared with the SIGMA‐ ε $ε $ model. Plain Language Summary: Geomagnetic storm is characterized by strong geomagnetic disturbances caused by solar energy eruption. During the geomagnetically quiet days, the global navigation satellite system (GNSS) precise point positioning (PPP) using the international GNSS service (IGS) precision products and dual‐frequency observations can achieve decimeter or even centimeter level positioning accuracy. However, during the severe geomagnetic storm, the ionospheric disturbances can decrease the quality of GNSS measurements or even cause the signals loss of lock. Though it is difficult to ensure the accuracy and availability of PPP by using traditional GNSS data processing models and methods, in this study, we focus on improving the stochastic model to mitigate the storm effects on GNSS PPP. An improved stochastic model based on rate of total electron content index is established in this study. The PPP experiment is carried out by using abundant GNSS datasets from global IGS stations. Results indicate that the improved stochastic model can effectively improve the positioning accuracy under severe geomagnetic storm conditions. Key Points: Current stochastic models of global navigation satellite system (GNSS) precise point positioning (PPP) do not properly consider the storm effects Rate of total electron content index (ROTI) based stochastic model is established to mitigate severe storm effects on GNSS PPP Positioning accuracy of GNSS PPP based on ROTI‐based stochastic model is generally better than that of PPP with common stochastic models