Draft:GNSS Interferometric Reflectometry

GNSS Interferometric Reflectometry, or GNSS-IR, is an environmental sensing method that uses a GNSS receiver with a zenith pointing antenna to measure variables such as snow depth, soil moisture content, tides and surface elevation. . This ground-based technique is similar but distinct from GNSS Reflectometry (GNSS-R), which uses space-based receivers to extract properties of ground-reflected GNSS signals.

The strength of this technique is that it employs commonly-used static ground-based GNSS receivers, such as those used for crustal deformation studies, reference datums, and RTK service providers without any required modifications to the instrument setup, meaning that thousands of existing GNSS stations globally can be leveraged to provide additional environmental parameters. The primary requirement is that the surrounding surfaces around the instrument are relatively planar.

For any given direct signal from a GNSS satellite, that signal also reflects off of the surrounding surface in a phenomenon called multipath. When the reflecting surface is near planar, that reflection wave largely retains its coherence, and the reflected signal interferes with the direct signal, constructively or destructively, creating an interference-like sinusoidal pattern in the SNR measurable for that satellite. Put another way, as the satellite rises in the sky, the relative path length between the direct and reflected signals changes such that they at times constructively interfere, and other times destructively interfere, creating a sinusoidal pattern in signal strength as a function of the satellite elevation angle. The frequency of this sinusoid is resultant primary measurable of interest, which is in turn driven by the antenna height above the reflecting surface, commonly denoted as $$R_h$$. Thus, $$R_h$$ can be derived by analyzing the frequency of the SNR signal, typically by using a Lomb-Scargle Periodogram.

With the size of the GNSS constellations, there can be hundreds of satellite arcs in a given day, allowing for many simultaneous or near-simultaneous estimates of $$R_h$$. This can be used to track snow depth changes or daily tides or water levels, whereby the snow or water reflection surfaces are changing in time. Other aspects of the SNR measurements can be exploited for environmental parameter extraction, such as the phase of the SNR sinusoid, which can be connected to the moisture content of the reflecting surface