This effort presents the development of a multi-sensor suite to analyze GNSS reflected signal characteristics as a function of surface conditions of Lake Michigan. The purpose of this sensor system is ultimately to determine how to use GNSS-R to monitor and distinguish liquid freshwater from lake ice, paving the way for routine remote sensing of seasonal ice formation. The sensor suite integrates disparate data sets, comparing the detection of GNSS-R at an elevated ground-based site to auxiliary data sets on collocated weather and surface conditions, using ground-based lidar and optical camera, in addition to satellite-based remote sensing imagery. Initial tests in the lab are conducted on the universal software radio peripherals (USRPs) that are to serve as the GNSS front-ends for data collection campaigns. The test uses a simulated L1 GPS signal, with a GPS antenna connected to serve as a discipline for the USRP’s oscillator. Initial testing of the lidar is also conducted in the lab. This experiment characterizes the lidar range and intensities from a variety of controlled surfaces mounted 1 m away from the lidar: an empty pan, still water 5 cm in depth, the same water disturbed, and ice. The USRP tests produce the power spectral density of the GPS L1 signal, but the time domain digitized data give a bi-modal rather than Gaussian histogram. Lidar range and intensity data are received from both the ice and water surfaces, with variations that correspond to the medium tested.