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  • English  (4)
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  • 1
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    Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations (2022)
    In:  IEEE Transactions on Geoscience and Remote Sensing
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    Publication Date: 2023-01-30
    Description: For the first time, rain effects on the polarimetric observations of the global navigation satellite system reflectometry (GNSS-R) are investigated. The physical feasibility of tracking the modifications in the surface roughness by rain splash and the surface salinity by the accumulation of freshwater is theoretically discussed. An empirical analysis is carried out using measurements of a coastal GNSS-R station with two side-looking antennas in right- and left-handed circular polarizations (RHCP and LHCP). Discernible drops in RHCP and LHCP powers are observed during rain over a calm sea. The power drop becomes larger at higher elevation angles. The average LHCP power drops by ≈ 5 dB at an elevation angle of 45°. The amplitude of the correlation sum shows a dampening, responding to rain rate systematically. The LHCP observations show higher sensitivity to rainfall compared to RHCP observations. The retrieved standard deviation of surface heights shows a steady increase with the rain rate. The derived surface salinity shows a decrease at rains higher than 10 mm/h. This study confirms the potential under environmental conditions of the GNSS-R ground-based station, e.g., with salinity mostly lower than 30 psu, over a calm sea, being a starting point for future investigations.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 2
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    Improving tropospheric corrections on large-scale Sentinel-1 interferograms using a machine learning approach for integration with GNSS-derived zenith total delay (ZTD) (2020)
    In:  Remote Sensing of Environment
    Details
    Publication Date: 2020-12-10
    Description: Sentinel-1 mission with its wide spatial coverage (250 km), short revisit time (6 days), and rapid data dissemination opened new perspectives for large-scale interferometric synthetic aperture radar (InSAR) analysis. However, the spatiotemporal changes in troposphere limits the accuracy of InSAR measurements for operational deformation monitoring at a wide scale. Due to the coarse node spacing of the tropospheric models, like ERA-Interim and other external data like Global Navigation Satellite System (GNSS), the interpolation techniques are not able to well replicate the localized and turbulent tropospheric effects. In this study, we propose a new technique based on machine learning (ML) Gaussian processes (GP) regression approach using the combination of small-baseline interferograms and GNSS derived zenith total delay (ZTD) values to mitigate phase delay caused by troposphere in interferometric observations. By applying the ML technique over 12 Sentinel-1 images acquired between May–October 2016 along a track over Norway, the root mean square error (RMSE) reduces on average by 83% compared to 50% reduction obtained by using ERA-Interim model.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 3
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    A Performance Assessment of Polarimetric GNSS-R Sea Level Monitoring in the Presence of Sea Surface Roughness (2021)
    In:  Proceedings
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    Publication Date: 2023-07-24
    Description: Monitoring coastal sea level has gained a large socioeconomic and environmental significance. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) offers various geophysical parameters including sea surface height. We investigate a one-year dataset from January to December 2016 to evaluate the performance of GNSS-R coastal sea levels during different sea states. Our experiment setup uses three types of antenna in terms of polarization and orientation. A zenith-looking antenna tracks Right-Handed Circular Polarization (RHCP) direct signals and two sea-looking antennas capture both Left-Handed Circular Polarization (LHCP) and RHCP reflections. The Singular Spectrum Analysis (SSA) is used for extracting interferometric frequency from the data and calculating the heights. The results indicate that the height estimates from the sea-looking antennas have better accuracy compared to the zenith-looking orientation. The LHCP antenna delivers the best performance. The yearly Root Mean Square Errors (RMSE) of 5-min GNSS-R L1 water levels compared to the nearest tide gauge are 2.8 and 3.9 cm for the sea-looking antennas and 4.7 cm for the zenith-looking antenna with correlations of 97.63, 95.02, 95.35 percent, respectively. Our analysis shows that the roughness can introduce a bias to the measurements.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 4
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    Tidal harmonics retrieval using GNSS-R dual-frequency complex observations (2023)
    In:  Journal of Geodesy
    Details
    Publication Date: 2023-12-22
    Description: Tidal analysis and methods for estimation and prediction of ocean tidal constitutes are essential in a large area of scientific disciplines, for example, navigation, onshore and offshore engineering, and production of green energy. Ground-based Global Navigation Satellite System-Reflectometry (GNSS-R) has been proposed as an alternative method for measuring sea surface height. We use 6 years of GNSS-R observations at In-phase and Quadrature levels from July 2015 to May 2021 obtained from a dedicated receiver and sea-looking left hand circular polarization antenna for estimating sea level (SL). In the first step, the multivariate least-square harmonic estimation (LS-HE) method is applied for SL estimation. Then, final SL time series are generated by combining estimated SL from all satellites at L1 and L2 frequencies in the averaging step. The 6-year root-mean-square error between GNSS-R L12 sea surface heights and a collocated tide gauge (TG) is 5.8 cm with a correlation of 0.948 for a high temporal resolution of 5 min with 15 min averaging window. Afterward, using the univariate LS-HE, we detect tidal harmonics with periods between 30 min to 1 year. The detection results highlight a good match between GNSS-R and TG. Higher harmonics, i.e., the periods shorter than 3 h, show stronger signatures in GNSS-R data. Finally, we estimate the amplitude and phase of standard tidal harmonics from the two datasets. The results show an overall good agreement between the datasets with a few exceptions.
    Language: English
    Type: info:eu-repo/semantics/article
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