GNSS remote sensing of the PRETTY CubeSat mission: a demonstration to validate models of ionospheric electron density

Kurzfassung

The L-band signals of Global Navigation Satellite Systems (GNSS) provide position, velocity and timing services to a global user community. The correction of ionospheric delays in L-band plays a crucial role for these services, for example, to reach sub-meter (or better) position accuracy. The crucial role of ionosphere and neutral atmosphere in GNSS signal propagation gave rise to respective remote sensing applications of GNSS. Among other parameters, the ionospheric electron content above the satellite orbit can be retrieved using satellite-based GNSS observations. The Passive REflecTometry and dosimeTrY (PRETTY) mission is a 3-unit CubeSat that has been launched into a low Earth orbit, of about 564 km altitude, on 9th October 2023. Its main payload is GNSS receiver that exploits the reflected GNSS signals for remote sensing with main focus altimetry. The goal is to derive the height of the specular reflection point on the Earth surface with a sub-meter accuracy. The ionospheric correction is especially important in this case as corresponding delays occur on the two involved signal paths: the direct one and the reflected one. Particularly, the electron content below the satellite orbit contributes to the delay. We demonstrate in our current work the retrieval of ionospheric delays from PRETTY observations and the comparison of retrieved delays with modelled values assuming state-of-the-art electron density models: the Neustrelitz Electron Density Model (NEDM2020), the NeQuick Model and the International Reference Ionosphere (IRI 2016). The comparison shows that for grazing GNSS observations (towards the Earth limb) the different model results vary on the meter-scale and that the retrieved delays lie within this range. We conclude that the delay retrieval can help to validate existing electron density models and to identify weak points for model improvement. An on-going task is to analyze differences among the models and to quantify retrieval uncertainties of other factors (satellite orbits, neutral atmosphere and reflection point location). Potentially, also other small satellites can provide reflectometry observations to validate ionosphere models (e.g. CyGNSS and the upcoming HydroGNSS mission).