A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning

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 acousti...

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Main Authors: Pierre Sakic, Valérie Ballu, Jean-Yves Royer
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/3/448
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author Pierre Sakic
Valérie Ballu
Jean-Yves Royer
author_facet Pierre Sakic
Valérie Ballu
Jean-Yves Royer
author_sort Pierre Sakic
collection DOAJ
description 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 <i>Python3</i> used in this article are freely available online.
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spelling doaj.art-7e79a778d634404c86d4a155a57dd0832022-12-21T19:42:09ZengMDPI AGRemote Sensing2072-42922020-02-0112344810.3390/rs12030448rs12030448A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor PositioningPierre Sakic0Valérie Ballu1Jean-Yves Royer2CNRS &amp; University of La Rochelle, Littoral Environnement et Sociétés, 2 Rue Olympe de Gouges, 17000 La Rochelle, FranceCNRS &amp; University of La Rochelle, Littoral Environnement et Sociétés, 2 Rue Olympe de Gouges, 17000 La Rochelle, FranceCNRS &amp; University of Brest, Laboratoire Géosciences Océan, Institut Universitaire Européen de la Mer, Rue Dumont d’Urville, 29280 Plouzané, FranceMonitoring 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 <i>Python3</i> used in this article are freely available online.https://www.mdpi.com/2072-4292/12/3/448seafloor geodesyoffshore geodesyabsolute seafloor positioninggnss-acousticsimulationsleast-squares inversionacoustic two-way-travel timesdepth differencesbaseline lengths
spellingShingle Pierre Sakic
Valérie Ballu
Jean-Yves Royer
A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
Remote Sensing
seafloor geodesy
offshore geodesy
absolute seafloor positioning
gnss-acoustic
simulations
least-squares inversion
acoustic two-way-travel times
depth differences
baseline lengths
title A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
title_full A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
title_fullStr A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
title_full_unstemmed A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
title_short A Multi-Observation Least-Squares Inversion for GNSS-Acoustic Seafloor Positioning
title_sort multi observation least squares inversion for gnss acoustic seafloor positioning
topic seafloor geodesy
offshore geodesy
absolute seafloor positioning
gnss-acoustic
simulations
least-squares inversion
acoustic two-way-travel times
depth differences
baseline lengths
url https://www.mdpi.com/2072-4292/12/3/448
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