Towards Evolutionary Optimisation
for High Resolution Bathymetry
from SideScan Sonars
Geophysical
Laboratory, Aristotle University of Thessaloniki,
avgerinos1@hotmail.com , gtsokas@geo.auth.gr
(Received
Abstract: The main objective of this
paper is to use genetic algorithms in order to improve the quality of the
bathymetry derived from sidescan raw data. The optimisation sequence starts
with inverse modelling of the phase data, which uniquely corresponds to the
characteristics of the coupled system of the sidescan vehicle and the seafloor
terrain. These phase data are then compared with phase data actually collected
by the sonar, to produce a correlation coefficient as an objective
function. Simulation results are
reported for the algorithm showing robust convergence towards the optimum value
of the objective function. The results indicate that this new approach can be
used to avoid difficulties widely encountered during forward processing of
phase data to derive bathymetry