S.M. Jesus sjesus@ualg.pt
UCEH - Universidade do Algarve,
Campus de Gambelas, PT-8000,
Faro, Portugal.
A. Caiti andy@dist.unige.it
DIST - Universita di Genova
Via Opera Pia 13, IT-16145
Genova, Italia
Comments: download pdf file .
Ref.: Journal of Computational Acoustics, Vol.4, No.
3, p.273-290, 1996.
Abstract
Estimating the seabottom geophysical structure from the analysis of
acoustic returns of an explosive source (air-gun, sparker,...) has been
used for a longtime as a routine survey technique. Recent work showed
the possibility of using well-suited numerical models to invert the
acoustic field for estimating detailed geoacoustic sediment properties.
Common implementations used long synthetic aperture arrays (up to 2 km
and more) in order to resolve potential environmental ambiguities of
the acoustic field. Others, used vertical arrays of sensors covering a
significant part of the water column to identify the channel normal
mode structure and thus gather information for the bottom physical
relevant properties. This paper investigates, with simulated data, the
concept of using a moderate aperture physical line array and a sound
source simultaneously towed by a single ship for inverting the bottom
geoacoustic structure from the acoustic returns received on the array.
First, bottom parameter estimators are derived and their system
sensitivity is investigated. In particular, it is shown that such a
system may be used to sense compressional and shear velocities on the
bottom first layers. Density and attenuations (both compressional and
shear) have in general small influence on the acoustic field structure
and are therefore difficult to estimate. Increasing the signal
frequency bandwidth by incoherent module averaging has no significant
influence on sensitivity. Mismatch cases, mainly those related to
array/source relative position, showed that deviations of more than
$\lambda/3$ in range and
$\lambda/5$ in depth may give erroneous extremum location and therefore
biased final estimates. Second, two bottom parameter estimators are
compared and their performance tested on a typical shallow water
environment. In order to solve the underlying multiparameter inverse
problem, global search optimization is used. In particular, it is shown
that the use of an adaptive genetic algorithm may, in conjunction with
a well suited maximum likelihood based parameter estimator, rapidly
converge to the surface extremum. Inversion results are in agreement
with the predictions obtained from the sensitivity study. The mean
relative error at 10 dB signal-to-noise ratio
is within 1\% for the compressional velocity, while greater errors are
reported for the shear velocity. Comparison with recent results
obtained with a radial basis functions (RBF) inversion strategy showed
similar performance.
Finally, results obtained with a 156 m aperture towed array showed a
good agreement between the inverted compressional velocities
and the ground truth measurements.
ACKNOWLEDGMENT: this work was partially supported by the EU project MAS2-CT920022.