Exploration of Spaceborne Coherent GNSS Reflectometry for High Resolution Hydrological and Ice Observation

Soil moisture is an Essential Climate Variable (ECV) closely associated with hydrology, weather, agriculture and climate change, and that has potential for improved measurement from space. GNSS Reflectometry has been demonstrated as a new Earth Observation technique, and Surrey’s GNSS-Reflectometry instrument has been used on TechDemoSat-1, DoT-1 and NASA CYGNSS to measure ocean winds, and reflections are also retrieved over land and ice. SSTL leads a consortium in the ESA Scout HydroGNSS mission concept.

GNSS Reflections retrieved over the Amazon show the unique property of highlighting rivers underneath the rain forest canopy. The resolution of GNSS reflections is assumed to be around 25 km over the ocean, but when there is a flat surface, the reflections become coherent, and the resolution approaches the Fresnel zone of about 500 metres. The improved resolution could help map jungle river over-banking (an important source of methane), and sea ice edges. Coherent reflectometry may improve freeze / thaw monitoring over permafrost, and open the door for altimetry using GNSS, and for target detection of objects with reflective surfaces.

The processing scheme currently used on the instruments assumes that signals are not coherent, but are incoherent, and crucial information such as carrier phase is not being collected. This PhD studentship will investigate alternative processing schemes for collecting coherent signals from GPS and the wider bandwidth Galileo signals. Raw data collected by TechDemoSat-1 can be used to test new signal processing schemes, and there is the potential for involvement and implementation of algorithms on the DoT-1 and HydroGNSS satellite missions. Challenges include: open loop capture of coherent signals, radiometric correction of measurements, allowing for noise, and calibration and validation of measurements against in-situ or other sources of data and practical implementation in an embedded signal processing instrument that can be operated in orbit.

The candidate must have a strong aptitude and preferably experience with signal processing theory and practice. Detailed knowledge of at least one of Earth Observation Radar, GNSS signals, FPGAs, C-programming will be essential. The student should hold a good first degree or Master’s level degree in electronic engineering, spacecraft engineering or a physical science.

CASE studentship available to UK Residency only.

IELTS requirements: English language requirements: IELTS 6.5 or above (or equivalent) with 6.0 in each individual category.

Surrey Space Centre - On-board data handling, Remote Sensing Applications

Student to be embedded in SSTL