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Provedor de dados:  ArchiMer
País:  France
Título:  A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
Autores:  Sakic, Pierre
Ballu, Valerie
Royer, Jean-yves
Data:  2020-02
Ano:  2020
Palavras-chave:  Seafloor geodesy
Offshore geodesy
Absolute seafloor positioning
GNSS-Acoustic
Simulations
Least-squares inversion
Acoustic two-way-travel times
Depth differences
Baseline lengths
Resumo:  Monitoring deformation on the seafloor is a major challenge for modern geodesy and a key to better understanding tectonic processes and assess related hazards. The extension of the geodetic networks offshore can be achieved by combining satellite positioning (GNSS) of a surface platform with acoustic ranging to seafloor transponders. This approach is called GNSS-Acoustic (GNSS-A). The scope of this work is to provide a tool to identify and quantify key points in the error budget of such experiment. For this purpose, we present a least-squares inversion method to determine the absolute position of a seafloor transponder array. Assuming the surface platform is accurately positioned by GNSS, the main observables are the two-way travel time in water between the transponders on the seafloor and the surface platform acoustic head. To better constrain transponder positions, we also consider the baseline lengths and the relative depth-differences between different pairs of them. We illustrate the usefulness of our forward modeling approach and least-square inversion by simulating different experimental protocols (i.e., platform trajectories, with or without information on the distance and depth between transponders). We find that the overall accuracy of a GNSS-A experiment is significantly improved with additional information about the relative depths of the instruments. Baseline lengths also improve the accuracy, but only when combined with depth differences. The codes in Python3 used in this article are freely available online.
Tipo:  Text
Idioma:  Inglês
Identificador:  https://archimer.ifremer.fr/doc/00659/77080/78401.pdf

https://archimer.ifremer.fr/doc/00659/77080/78402.pdf

DOI:10.3390/rs12030448

https://archimer.ifremer.fr/doc/00659/77080/
Editor:  Mdpi
Formato:  application/pdf
Fonte:  Remote Sensing (Mdpi), 2020-02 , Vol. 12 , N. 3 , P. 448 (19p.)
Direitos:  info:eu-repo/semantics/openAccess

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