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doi: 10.3390/rs12030448
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.
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, 550, Atmosphere, [PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, depth differences, Science, least-squares inversion, Q, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], absolute seafloor positioning, acoustic two-way-travel times, offshore geodesy, baseline lengths, GNSS-Acoustic, gnss-acoustic, seafloor geodesy, simulations, seafloor geodesy; offshore geodesy; absolute seafloor positioning; GNSS-Acoustic; simulations; least-squares inversion; acoustic two-way-travel times; depth differences; baseline lengths
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, 550, Atmosphere, [PHYS.PHYS.PHYS-GEO-PH] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, depth differences, Science, least-squares inversion, Q, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], absolute seafloor positioning, acoustic two-way-travel times, offshore geodesy, baseline lengths, GNSS-Acoustic, gnss-acoustic, seafloor geodesy, simulations, seafloor geodesy; offshore geodesy; absolute seafloor positioning; GNSS-Acoustic; simulations; least-squares inversion; acoustic two-way-travel times; depth differences; baseline lengths
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |