TY - JOUR T1 - Regional Ionosphere Delay Models Based on CORS Data and Machine Learning JF - NAVIGATION: Journal of the Institute of Navigation JO - NAVIGATION DO - 10.33012/navi.577 VL - 70 IS - 3 SP - navi.577 AU - Randa Natras AU - Andreas Goss AU - Dzana Halilovic AU - Nina Magnet AU - Medzida Mulic AU - Michael Schmidt, AU - Robert Weber Y1 - 2023/09/21 UR - https://navi.ion.org/content/70/3/navi.577.abstract N2 - The ionospheric refraction of GNSS signals can have an impact on positioning accuracy, especially in cases of single-frequency observations. Ionosphere models that are broadcasted by the satellite systems (e.g., Klobuchar, NeQuick-G) do not include enough details to permit them to correct single-frequency observations with sufficient accuracy. To address this issue, regional ionosphere models (RIMs) have been developed in several countries in the western Balkans based on dense Continuous Operating Reference Stations (CORS) observations. Subsequently, a RIM for the western Balkans was built using an artificial neural network that combined regional ionosphere parameters estimated from the CORS data with spatiotemporal (latitude, longitude, hour of day), solar (F10.7) and geomagnetic (Kp, Dst) parameters. The RIMs were tested at the solar maximum (March 2014), a geomagnetic storm (March 2015), and the solar minimum (March 2018). The new RIMs mimic the integrated electron density much more effectively than the Klobuchar model. Furthermore, RIMs significantly reduce the ionospheric effects on single-frequency positioning, indicating their necessity for use in positioning applications. ER -