Abstract
Various object functions for broadband inversions of noisy data using matched-field processing for bottom recognition are studied. The study is based on the inversion results obtained by processing synthetic ‘‘noisy’’ data that have been available at a follow-up stage of a benchmark exercise for bottom geoacoustic inversions that was carried out in 1997 (Vancouver, Canada). A genetic algorithm has been used for the implementation of the matched-field processing. The different behavior of the various processors that has already been observed by the authors at the benchmark exercise based on noise-free data is now considered with data that include noise, and their applicability for bottom recognition is analyzed.
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