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Ref.: PhD Thesis, University of Algarve, June 2015
Abstract:
Maritime rapid environmental assessment exercises became rather important. An underlying objective is
to predict the evolution of the acoustic field due to an underwater target. Main contributions to this
end have relied on accurate models of acoustic propagation, which receive baseline properties
and ocean forecasts as input. Intuitively, the most accurate oceanographic forecast should imply the
most accurate acoustic forecast. This can fail, due to at least two reasons: 1) the full set of
(space-time-variant) environmental properties are rarely known with enough accuracy; 2) even the most
sophisticated propagation model cannot handle the full environmental detail in solving propagation
equations, forcing the experimenter to reduce complex environmental features to a simplified
representation. Acoustic modelling errors appear then as inevitable. Little possibility of error minimization
exists, if the propagation model is simply run in a 'forward' manner. The results presented in this work
show that the acoustic error can be minimized, if the propagation model is fed with an environmental parameter
vector containing two distinct sets: one, fixed and formed by the environmental parameters with uncontrolled
errors; the other, variable and with errors determined in a controlled way, adapted to the errors in the first
subset. Here, the second set is treated as a distinct quantity, labelled as "equivalent model". It can be
determined by acoustic inversion. The equivalent model is employed for two objectives: to estimate the acoustic
field at a given present time (now cast), and a given future time (forecast). Synthetic acoustic fields, and
oceanographic measurements and predictions (with the Navy Coastal Ocean Model) obtained for the Maritime
Rapid Environmental Assessment 2003 sea trial, drive the simulations. For the problem of now cast, the
equivalent model is determined at sparse transect points, and interpolated to points with no acoustic
measurements. For the problem of forecast, the equivalent model is furthermore 'extrapolated' to future time.
The 'extrapolation' consists of a mapping between sound speed profile and equivalent model. When providing
an estimate of the future sound speed at the mapping input, the estimate of the future equivalent model is
obtained. The proposed method led to a decrease of 3-5 dB in transmission loss estimation error, as compared
to standard procedures.
Keywords: acoustic propagation model, environmental mismatch,
matched-field processing, oceanographic forecast, support vector machine.