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Improving GNSS‐R sea level determination through inverse modeling of SNR data
Author(s) -
Strandberg Joakim,
Hobiger Thomas,
Haas Rüdiger
Publication year - 2016
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1002/2016rs006057
Subject(s) - gnss applications , tide gauge , reflectometry , geodesy , geodetic datum , remote sensing , standard deviation , sampling (signal processing) , inversion (geology) , geology , global positioning system , environmental science , sea level , computer science , mathematics , statistics , telecommunications , oceanography , time domain , paleontology , structural basin , detector , computer vision
This paper presents a new method for retrieving sea surface heights from Global Navigation Satellite Systems reflectometry (GNSS‐R) data by inverse modeling of SNR observations from a single geodetic receiver. The method relies on a B‐spline representation of the temporal sea level variations in order to account for its continuity. The corresponding B‐spline coefficients are determined through a nonlinear least squares fit to the SNR data, and a consistent choice of model parameters enables the combination of multiple GNSS in a single inversion process. This leads to a clear increase in precision of the sea level retrievals which can be attributed to a better spatial and temporal sampling of the reflecting surface. Tests with data from two different coastal GNSS sites and comparison with colocated tide gauges show a significant increase in precision when compared to previously used methods, reaching standard deviations of 1.4 cm at Onsala, Sweden, and 3.1 cm at Spring Bay, Tasmania.