Abstract
GNSS reflectometry, whilst originally envisaged for ocean wind speed sensing, has recently been shown to be sensitive to land parameters such as soil moisture. Soil moisture is an important variable for many use cases including climate change monitoring, and as such there is a need to reduce gaps in datasets of this variable collected by satellites. By implementation on small platforms, GNSS-R missions can address this need, but current instrumentation must be updated to allow prediction of reflection points over the land surface. This paper presents an algorithm for achieving this along with results from both software testing and initial on-board implementation on DoT-1. These show that when Delay-Doppler maps are generated using the new algorithm the peak reflected power is successfully captured (in line with platform constraints) in 55% of software tests, compared with just 10% for the current method. Telemetry from DoT-1 shows that the algorithm has been successfully incorporated into the flight software. Future tasks to verify the on-board performance and improve the algorithm further are also discussed.