Atmospheric model for GNSS reflectometry (AMGr)
Precise altimetry with the GNSS requires the modeling of signal propagation in Earth's atmosphere (Semmling et al., 2016). To date various models exist. Typically theses models are based on a number of simplifying assumptions, e.g., they are based on the assumption of a spherically layered atmosphere. The uncertainties of these models are difficult to quantify.
The goal within this project is the development of a sophisticated model. This model will be applicable for both ground-based and spaceborne reflectometry. The model will run with three-dimensional refractivity fields. The pressure, temperature and humidity fields are provided from the atmospheric reanalysis ERA5 . The electron density field will be taken from a climatological model, the latest version of the International Reference Ionosphere (IRI). Earth's magnetic field is provided from the 12th generation of the International Geomagnetic Reference Field (IGRF). The fast and rapid ray-trace algorithm developed by Zus et al., 2017 will be adapted. In addition a parameterized version for practical usage shall be developed.
These developments are utilized in the European Space Agency’s GNSS-R CubeSat mission PRETTY (passive reflectometry and dosimetry). The mission’s primary goal is to retrieve sea surface height using grazing angle observations. The PRETTY mission operates at a single frequency (L5) and therefore model-based ionospheric corrections are required.
References
Semmling, A. M., Leister, V., Saynisch, J., Zus, F., Heise, S., & Wickert, J. (2016). A phase‐altimetric simulator: Studying the sensitivity of Earth‐reflected GNSS signals to ocean topography. IEEE Transactions on Geoscience and Remote Sensing, 54( 11), 6791– 6802.
Zus, F., Z. Deng, S. Heise, and J. Wickert (2017): Ionospheric mapping functions based on electron density fields, GPS Solut., 21, 873–885, doi:10.1007/s10291-016-0574-5.
Dielacher, A.; Fragner, H.; Koudelka, O. (2022): PRETTY—Passive GNSS-Reflectometry for CubeSats. Elektrotech. Inftech. 139, 25–32.
