A Topographically-Accurate GNSS-R Reflection Point Predictor for on-Board Operational Processing

Research efforts have been turning in recent times to the use of Global Navigation Satellite System Reflectometry (GNSS-R) for sensing land parameters such as soil moisture and above ground biomass, which are essential for climate modelling. GNSS-R instrumentation to date has been designed with the purpose of sensing ocean parameters (e.g. wind speed). In order to enable operational, spaceborne GNSS-R missions for land-sensing, upgrades to instrumentation are required. One aspect is the prediction of reflection points, which over the land is affected by the presence of topography; a problem not encountered when predicting reflection points over the ocean. This paper presents an algorithm which enables accurate prediction of reflection points in areas of topography to enable real-time, on-board production of Delay-Doppler Maps of land reflected signals, a development which is critical for enabling operational land-sensing GNSS-R missions.