References of "Tabibi, Sajad 50003164"
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See detailTidal analysis of GNSS reflectometry applied for coastal sea level sensing in Antarctica and Greenland
Tabibi, Sajad UL; Geremia-Nievinski, Felipe; Francis, Olivier UL et al

in Remote Sensing of Environment (2020), 248

We retrieve sea levels in polar regions via GNSS reflectometry (GNSS-R), using signal-to-noise ratio (SNR) observations from eight POLENET GNSS stations. Although geodetic-quality antennas are designed to ... [more ▼]

We retrieve sea levels in polar regions via GNSS reflectometry (GNSS-R), using signal-to-noise ratio (SNR) observations from eight POLENET GNSS stations. Although geodetic-quality antennas are designed to boost the direct reception from GNSS satellites and to suppress indirect reflections from natural surfaces, the latter can still be used to estimate the sea level in a stable terrestrial reference frame. Here, typical GNSS-R retrieval methodology is improved in two ways, 1) constraining phase-shifts to yield more precise reflector heights and 2) employing an extended dynamic filter to account for the second-order height rate of change (vertical acceleration). We validate retrievals over a 4-year period at Palmer Station (Antarctica), where there is a co-located tide gauge (TG). Because ice contaminates the long-period tidal constituents, we focus on the main tidal species (daily and subdaily), by employing a deseasonalization filter. The difference between sub-hourly GNSS-R retrievals of the ocean surface and TG records has a root-mean-square error (RMSE) of 15.4 cm and a correlation of 0.903, while the tidal prediction has a RMSE of 1.9 cm and a correlation of 0.998. There is excellent millimetric agreement between the two sensors for most eight major tidal constituents, with the exception of luni-solar diurnal (K1), principal solar (S2), and luni-solar semidiurnal (K2) components, which are biased in GNSS-R due to the leakage of the GPS orbital period. We also compare the GNSS-R tidal constituents from seven additional POLENET sites, without co-located TG, to global and local ocean tide models. We find that the root-sum-square-error (RSSE) of eight major constituents varies between 26.0 cm and 56.9 cm for different models. Given that the agreement in tidal constituents between the TG and GNSS-R was better at Palmer Station, we conclude that assimilating the GNSS-R retrievals into tidal models would improve their accuracy in Antarctica and Greenland, provided that care is exercised to avoid the orbital period overtones and also sea ice. [less ▲]

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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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