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See detailRecent Advances on GNSS Multipath Reflectometry (GNSS-MR) for Sea and Lake Level Studies
van Dam, Tonie UL; Tabibi, Sajad UL; Geremia-Nievinski, F. et al

E-print/Working paper (2018)

Global navigation satellite system multipath reflectometry (GNSS-MR) has been used to exploit signals of opportunity at L-band for ground-based sea and lake level studies at several locations in the last ... [more ▼]

Global navigation satellite system multipath reflectometry (GNSS-MR) has been used to exploit signals of opportunity at L-band for ground-based sea and lake level studies at several locations in the last few years. Although geodetic-quality antennas are designed to boost the direct transmission from the satellite and to suppress indirect surface reflections, the delay of reflections with respect to the line-of-sight propagation can be used to estimate the water-surface level in a stable terrestrial reference frame. In this contribution, signal-to-noise ratio (SNR) observations from commercial off-the-shelf systems are used to retrieve water level at multiple constellations and modulations. We constrained phase-shifts so as yield more precise reflector heights and further corrected for the tropospheric propagation delays for greater accuracy. We assess GNSS-MR accuracy and precision in two cases. In the first one, using the inversion formal uncertainty and modulation-specific variance factors, reflector heights are combined and converted to water level at hourly epoch spacing and eight-hourly averaging window length. The RMSE between GNSS-MR and tide gauge (TG) records for a single station in the Great Lakes is 1.93 cm for a 12-year period. In the second case, we employ an extended dynamic model, taking tidal velocity and acceleration into account, which is applied for ten stations worldwide. Regression slope between GNSS-MR and TG exhibits a smaller deviation from the ideal 1:1 relationship, compared to the conventional dynamic model (with no acceleration). The RMSE between sub-hourly GNSS-MR and TG is 1.98 cm, with 0.998 correlation coefficient. Tidal constituents agree at the sub-mm level between GNSS-MR and TG. [less ▲]

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See detailStatistical Comparison and Combination of GPS, GLONASS, and Multi-GNSS Multipath Reflectometry Applied to Snow Depth Retrieval
Tabibi, Sajad UL; Geremia-Nievinski, Felipe; van Dam, Tonie UL

in IEEE Transactions on Geoscience and Remote Sensing (2017), (99),

Global navigation satellite system (GNSS) multipath reflectometry (MR) has emerged as a new technique that uses signals of opportunity broadcast by GNSS satellites and tracked by ground-based receivers to ... [more ▼]

Global navigation satellite system (GNSS) multipath reflectometry (MR) has emerged as a new technique that uses signals of opportunity broadcast by GNSS satellites and tracked by ground-based receivers to retrieve environmental variables such as snow depth. The technique is based on the simultaneous reception of direct or line-of-sight (LOS) transmissions and corresponding coherent surface reflections (non-LOS). Until recently, snow depth retrieval algorithms only used legacy and modernized GPS signals. Using multiple GNSS constellations for reflectometry would improve GNSS-MR applications by providing more observations from more satellites and independent signals (carrier frequencies and code modulations). We assess GPS and GLONASS for combined multi-GNSS-MR using simulations as well as field measurements. Synthetic observations for different signals indicated a lack of detectable interfrequency and intercode biases in GNSS-MR snow depth retrievals. Received signals from a GNSS station continuously operating in France for a two-winter period are used for experimental snow depth retrieval. We perform an internal validation of various GNSS signals against the proven GPS-L2-C signal, which was validated externally against in situ snow depth in previous studies. GLONASS observations required a more complex handling to account for topography because of its particular ground track repeatability. Signal intercomparison show an average correlation of 0.922 between different GPS snow depths and GPS-L2-CL, while GLONASS snow depth retrievals have an average correlation that exceeds 0.981. In terms of precision and accuracy, legacy GPS signals are worse, while GLONASS signals and modernized GPS signals are of comparable quality. Finally, we show how an optimal multi-GNSS combined daily snow depth time series can be formed employing variance factors with a ~59%-90% precision improvement compared to individual signal snow depth retrievals, resulting in snow depth retrieval with uncertainty of 1.3 cm. The developed combination strategy can also be applied for the European Galileo and the Chines BeiDou navigation systems. [less ▲]

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See detailAssessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications
Tabibi, Sajad UL; Nievinski, Felipe G.; van Dam, Tonie UL et al

in Advances in Space Research (2015), 55(4), 1104-1116

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