Detection of Surface Lake Ice with GNSS Reflectometry
Roohollah Parvizi, James Henry, Norikazu Honda, Boris S. Pervan, and Seebany Datta-Barua, Illinois Institute of Technology
Much remote sensing of Earth’s cryosphere, regions of the surface environment that are frozen, focuses on sea ice because of its impact on the global water cycle and climate implications. Unlike sea ice, whose salinity increases density and slows the freezing process, lake ice forms on the surface because freshwater becomes less dense when frozen. Wave motion can also affect the smoothness of the ice formations.
A remote sensing technique known as GNSS-reflectometry (GNSS-R) takes advantage of GNSS signals reflected off surfaces to infer properties of that reflecting surface. GNSS-R has been explored and demonstrated in the literature, but ice detections often focus on sea ice. In this work we detect and investigate the signal properties detected from freshwater ice. Specifically, this paper presents preliminary results detecting GNSS signals reflected off surface ice of Lake Michigan. A ground-based multi-sensor system is sited on the shore of Lake Michigan. The data are collected in field campaigns from the same site on multiple dates. A test demonstration of the system was previously discussed in  with a controlled environment (artificial body of water) experiment.
Specular reflection point locations as a function of time are forecast, and along with local weather forecasts, used to plan each field campaign. The sensors include a zenith GNSS antenna and universal software radio peripheral (USRP) front end, a GNSS reflection antenna with USRP, a lidar, optical camera, and weather station. The sensors are mounted on a tripod sited on the shorefront of Lake Michigan. Data are collected and post-processed in the lab with the use of a software defined receiver (SDR). The scatter in signal power over delay and Doppler frequency is measured using a delay-Doppler map (DDM). The DDM is compared to lidar scans of the ice surface mapped to camera images of the shoreline and post-processed estimates of specular point locations, based on the zenith antenna position. We compare and analyze DDMs for different ice surface conditions with an eye toward building a freshwater ice GNSS-R database.
 Parvizi, R., J. Henry, N. Honda, B. S. Pervan, and S. Datta-Barua, “Coordination of GNSS Signals with LiDAR for Reflectometry,” Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, in press.