C. Soares csoares@ualg.pt
S.M. Jesus sjesus@ualg.pt
A. Mantouka, amantouka@ualg.pt
P. Felisberto, pfelis@ualg.pt
LARSys, University of Algarve,
Campus de Gambelas, PT-8005-139 Faro, Portugal.
Comments: download pdf file (not available).
Ref.: MTS/IEEE Oceans, Aberdeen, June 2017.
Abstract
The WiMUST (Widely scalable Mobile Underwater Sonar Technology) Project envisions using a team of autonomous
underwater vehicles towing short acoustic arrays for seismic surveying of seabottom geoacoustic properties.
One of the objectives in the project is to tackle the inversion of acoustic data collected with short towed
horizontal arrays by means of a Matched-Field Inversion (MFI) technique. While there is great deal of
experience in MFI and the so-called focalization applied to horizontal propagation scenarios, in near vertical
propagation scenarios, with a source receiver horizontal distance limited to a few tens of meter or less, there
is little understanding in terms of feasibility of the acoustic inversion of bottom properties. In particular,
the simultaneous inversion of bottom properties (sound speeds, densities, attenuations) of multiple bottom layers
has to be tackled, since the experimenter has to account for the admissible mismatch of other environmental
properties such as water sound speed and depth, and the potential solution ambiguity inherent to an optimization
problem with ten or more unknown parameters. The actual simulation study, carried out with an environmental
scenario and geometric set up based on the Peljesac data set, considers a shallow water acoustic propagation
scenario with a short array. A sensitivity analysis in MFI provides understanding on the observability of the
unknown parameters of interest. A mismatch analysis indicates that water column mismatch (sound speed and depth)
may cause the MFI procedure to break down. Based on the conclusions taken from the sensitive and mismatch analysis,
an iterative acoustic inversion concept with feedback of intermediate parameter estimates is developed and tested
with simulated data.
ACKNOWLEDGMENT: This work was funded under project WiMUST contract 645141, H2020 program of the EU.
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