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Session C2: Advances in High Accuracy Positioning

Spherical Harmonics Ionospheric Modelling, a Lever for Regional and Global High-Accuracy Services
N. Pérez, J. Durán, L. Martinez, E. Carbonell, A. Chamorro, D. Calle, I. Rodriguez GMV
Date/Time: Wednesday, Sep. 18, 2:35 p.m.

PPP-RTK (Precise Point Positioning-Real Time Kinematics) is a technique used for precise positioning that relies on a single receiver to determine its high accuracy position by processing signals from multiple satellite constellations (e.g., GPS, GLONASS, Galileo, BeiDou) and accounting for various error sources, including satellite clock errors, orbital errors, and atmospheric effects such as ionospheric delay. PPP requires precise knowledge of the satellite orbits and clocks, as well as corrections for atmospheric effects like ionospheric delay, tropospheric delay, and other factors. Without accurate ionospheric correction, PPP accuracy and convergence time can be significantly affected.
Charged particles found within the ionosphere cause disturbances in radio waves, including those transmitted by GPS, Galileo, or BeiDou systems, leading to inaccuracies beyond what navigation models usually are able to predict for users. The delay in the signal due to this interference typically leads to a slow convergence of PPPs algorithms employing sequential filters to the decimeter level. The impact of the delay caused by the transit of the signal trough the ionosphere varies depending on the user's geographical location and solar activity. Therefore, creating a precise global model that remains accurate across diverse regions, seasons, and timeframes presents a considerable challenge. High Accuracy positioning algorithms use models to estimate and correct for ionospheric delay. These models often require precise information about the state of the ionosphere, which can be obtained from global ionospheric models or regional ionospheric monitoring networks.
The usage of regional ionospheric correction hinges on the requirement for a substantial number of GNSS stations. Typically, the distance between stations in a regional network utilized for this purpose ranges from 50 to 200 km. To effectively implement this method for services covering wide regions such as Europe or North America, the expense associated with acquiring and maintaining the necessary number of stations becomes the primary cost factor for the service.
The primary objective of this paper is to introduce a wide-area ionospheric model designed to refine the accuracy and decrease the convergence time of user positioning by precisely estimating and correcting ionospheric delays. This approach relies on a sophisticated mathematical foundation rooted in a spherical harmonic expansion model. One of the key advantages of this strategy is its ability to reduce the reliance on densely distributed station networks for continuous estimation of ionospheric delays. By implementing this method, the need for an extensive network of stations is mitigated, thereby streamlining the process, and enhancing the efficiency and reducing the cost of the service.
This paper presents an analysis of the density of the network needed to generate an ionospheric model that maximizes the accuracy and minimizes de convergence time of High Accuracy positioning solutions within a wide-area such as Europe. As starting point, a global network of around 30 GNSS stations around the globe will be used. Next, a gradual increase in the density of the network will be carried out by adding stations within the studied area to create an ionospheric model for each network under study. The denser network studied for Europe solution will have a baseline equivalent to EGNOS RIMS network.
To assess the effectiveness of these models in estimating the final user position, various Precise Point Positioning (PPP-RTK) solutions are computed at different locations within the designated area. These results are then compared with PPP-RTK solutions calculated at the same stations but without ionospheric corrections. The aim of this study is to demonstrate the notable enhancement in performance achieved through the integration of this ionospheric model.

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