Ionospheric delay is a significant error source in multi-GNSS positioning. We present different processing strategies to fully exploit the ionospheric delay effects on multi-frequency and multi-GNSS positioning performance, including standard point positioning (SPP) and precise point positioning (PPP) scenarios. Datasets collected from 10 stations over thirty consecutive days provided by multi-GNSS experiment (MGEX) stations were used for single-frequency SPP/PPP and dual-frequency PPP tests with quad-constellation signals. The experimental results show that for single-frequency SPP, the Global Ionosphere Maps (GIMs) correction achieves the best accuracy, and the accuracy of the Neustrelitz TEC model (NTCM) solution is better than that of the broadcast ionospheric model (BIM) in the E and U components. Eliminating ionospheric parameters by observation combination is equivalent to estimating the parameters in PPP. Compared with the single-frequency uncombined (UC) approach, the average convergence time of PPP with the external ionospheric models is reduced. The improvement in BIM-, NTCM- and GIM-constrained quad-constellation L2 single-frequency PPP was 15.2%, 24.8% and 28.6%, respectively. The improvement in convergence time of dual-frequency PPP with ionospheric models was different for different constellations and the GLONASS-only solution showed the least improvement. The improvement in the convergence time of BIM-, NTCM- and GIM-constrained quad-constellation L1/L2 dual-frequency PPP was 5.2%, 6.2% and 8.5%, respectively, compared with the UC solution. The positioning accuracy of PPP is slightly better with the ionosphere constraint and the performance of the GIM-constrained PPP is the best. The combination of multi-GNSS can effectively improve the positioning performance.

Precision and safety of life applications of Global Navigation Satellite Systems require key information on space weather conditions in particular on the perturbation degree of the ionosphere. Such systems are particularly vulnerable against severe spatial gradients and rapid changes of the total electron content (TEC) measured along different satellite‐receiver links. To estimate spatial gradients and rapid temporal variations of ionospheric TEC, two approaches are discussed. The Gradient Ionosphere indeX (GIX) and the Sudden Ionospheric Disturbance indeX are able to estimate the perturbation degree of the ionosphere instantaneously without taking into account previous measurements. The capabilities and accuracy of the index approaches are demonstrated by simulations using a 3‐D electron density model of the ionosphere and plasmasphere in conjunction with realistic Global Navigation Satellite Signal constellations. Real data tests confirm the applicability of GIX and the related standard deviation GIX Sigma to monitor spatial gradients. Sudden Ionospheric Disturbance indeX is able to monitor rapid temporal variations of TEC as exemplified by using Global Navigation Satellite Signal measurements carried out during solar flare events. Both approaches could identify enhanced space weather impacts on precise point positioning and the European Geostationary Navigation Overlay Service. More comprehensive studies analyzing ionospheric storms in close dialogue with potential customers are needed to fully utilize the potential of these approaches to serve as objective ionospheric indices for scaling horizontal TEC gradients and rapid TEC variations in space weather services.

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