Underwater Target Localization and Estimation of Ocean Environmental Parameters Using a Genetic Algorithm
conference paper
In the field of underwater acoustics the signal processing technique " Matched Field
Inversion" (MFI) has become a major topic during the last years. This technique
can be used for determining both target location and parameters describing the
ocean environment. When using MFI, the measured underwater acoustic field
is compared with the acoustic field that is predicted by an acoustic model for
a certain set of the unknown model parameters, such as target location and geoacoustic
ocean bottom parameters. An energy function providing a measure for the
similarity between the two acoustic fields is defined. By now minimizing the energy
function, the set of input parameters corresponding to the maximum similarity
between both acoustic fields, i.e. the solution, is found. Due to the extremely
large number of possible parameter value combinations and the occurrence of local
minima, global optimization methods are required to solve this inverse problem.
As the global search method, a genetic algorithm has been applied.
Inversion" (MFI) has become a major topic during the last years. This technique
can be used for determining both target location and parameters describing the
ocean environment. When using MFI, the measured underwater acoustic field
is compared with the acoustic field that is predicted by an acoustic model for
a certain set of the unknown model parameters, such as target location and geoacoustic
ocean bottom parameters. An energy function providing a measure for the
similarity between the two acoustic fields is defined. By now minimizing the energy
function, the set of input parameters corresponding to the maximum similarity
between both acoustic fields, i.e. the solution, is found. Due to the extremely
large number of possible parameter value combinations and the occurrence of local
minima, global optimization methods are required to solve this inverse problem.
As the global search method, a genetic algorithm has been applied.
Topics
TNO Identifier
95101
Publisher
World Scientific
Source title
Fuzzy Logic and Intelligent Technologies for Nuclear Science and Industry - Proceedings of the 3rd International FLINS Workshop, Antwerp, Belgium, September 14-16, 1998
Editor(s)
Ruan, D.
Abderrahim, H.A.
D'hondt, P.
Kerre, E.E.
Abderrahim, H.A.
D'hondt, P.
Kerre, E.E.
Place of publication
Singapore
Pages
276-285
Files
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