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Global Positioning System (GPS) signal-to-noise ratio (SNR) measurements can be employed to retrieve environmental variables in multipath reception conditions, whereby direct or line-of-sight transmission is received simultaneously with coherent reflections thereof. Previous GPS SNR multipath studies of soil moisture and snow depth have focused on the legacy GPS L1 and L2 bands. In the present paper, short-delay, near-grazing incidence multipath from the L5-band GPS SNR is assessed for its value in detecting soil moisture and snow depth. The L5 signal will become more important in the future because of compatibility and interoperability among the different global satellite navigation systems. The L5 results are compared with L2C estimates to determine whether the L2C-L5 differences (given their differing power budgets and their modulation properties) are significant. To address these questions, measurements and simulations were employed. A physically-based multipath simulator was enhanced to investigate the differences between parameter retrievals for the L2C and the L5 GPS signals. Parameter retrievals from synthetic observations for different scenarios were compared. Comparisons included varying reflector height, surface material, and surface roughness. Measurements from two GPS stations in Colorado, USA, were used to retrieve soil moisture and snow depth conditions. Over a 153-day period that encompassed the catastrophic 2013 Colorado flooding event, L2-derived volumetric soil moisture had an RMS difference of 0.042 cm 3 /cm 3 while the L5 RMS difference was 0.034 cm 3 / cm 3 with respect to in-situ data (values of volumetric soil moisture range between 0.04 and 0.34 cm 3 /cm 3 ). In a separate 483-day campaign, L5-derived snow depth estimates were compared to L2C-derived values and found strongly correlated, deviating from a one-toone relationship by only 0.00001 ± 0.0064 cm/cm. These results indicate the absence of any detectable biases in L5 as compared to L2C for retrieving soil moisture and snow depth from GPS SNR multipath observations.

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Global navigation satellite system reflectometry (GNSS-R) uses signals of opportunity in a bi-static configuration of L-band microwave radar to retrieve environmental variables such as water level. The line-of-sight signal and its coherent surface reflection signal are not separate observables in geodetic GNSS-R. The temporally constructive and destructive oscillations in the recorded signal-to-noise ratio (SNR) observations can be used to retrieve water-surface levels at intermediate spatial scales that are proportional to the height of the GNSS antenna above the water surface. In this contribution, SNR observations are used to retrieve water levels at the Vianden Pumped Storage Plant (VPSP) in Luxembourg, where the water-surface level abruptly changes up to 17 m every 4-8 h to generate a peak current when the energy demand increases. The GNSS-R water level retrievals are corrected for the vertical velocity and acceleration of the water surface. The vertical velocity and acceleration corrections are important corrections that mitigate systematic errors in the estimated water level, especially for VPSP with such large water-surface changes. The root mean square error (RMSE) between the 10-min multi-GNSS water level time series and water level gauge records is 7.0 cm for a one-year period, with a 0.999 correlation coefficient. Our results demonstrate that GNSS-R can be used as a new complementary approach to study hurricanes or storm surges that cause abnormal rises of water levels.

This article presents a review on spaceborne Global Navigation Satellite System Reflectometry (GNSS-R), which is an important part of GNSS-R technology and has attracted great attention from academia, industry and government agencies in recent years. Compared with ground-based and airborne GNSS-R approaches, spaceborne GNSS-R has a number of advantages, including wide coverage and the ability to sense medium- and large-scale phenomena such as ocean eddies, hurricanes and tsunamis. Since 2014, about seven satellite missions have been successfully conducted and a large number of spaceborne data were recorded. Accordingly, the data have been widely used to carry out a variety of studies for a range of useful applications, and significant research outcomes have been generated. This article provides an overview of these studies with a focus on the basic methods and techniques in the retrieval of a number of geophysical parameters and the detection of several objects. The challenges and future prospects of spaceborne GNSS-R are also addressed.

Geodetic Global Navigation Satellite System reflectometry (GNSS-R) uses ground-based signals of opportunity to retrieve sea levels at an intermediate spatial scale. Geodetic GNSS-R is based on the simultaneous reception of Line-of-Sight (LoS) and its coherent GNSS sea surface reflection (non-LOS) signals. The scope of this paper is to present geodetic GNSS-R applied to sea level altimetry. Signal-to-Noise Ratio (SNR) measurements from a Commercial Off-The-Shelf (COTS) geodetic-quality GNSS station at the Haiti Coast Guard Base in Port-au-Prince is used to retrieve sea levels in the International Terrestrial Reference Frame 2014 (ITRF2014). The GNSS-R sea levels are compared with those of the OTT Radar Level Sensor (RLS) installed vertically below the GNSS antenna. The Root-Mean-Square Error (RMSE) between the geodetic GNSS-R sea levels and OTT RLS records is 3.43 cm, with a correlation of 0.96. In addition, the complex differences between the OTT RLS records and 15-min GNSS-R sea levels using Global Positioning System (GPS) and Globalnaya Navigazionnaya Sputnikovaya Sistema (or Global Navigation Satellite System; GLONASS) signals for all the eight major tidal constituents are in mm-level agreement. Therefore, geodetic GNSS-R can be used as a complementary approach to the conventional method for sea level studies in a stable terrestrial reference frame.

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