Matched field processing: environmental focusing and source tracking with application to the North Elba data set

Experimental results on the localization of a moving sound source in shallow water are presented. Genetic algorithms (GA) are used to first intensively estimate the environment from a fixed source part of the data. Then, assuming the stationarity of the environment, localization is carried out in the moving source part of the data. Comparison with results obtained previously on the same data set shows that the source range error is reduced by 75%, while the source depth error is reduced by approximately 50%.