Bottom geoacoustic inversion by "broadband" matched-field processing

Matched-Field Processing with a Genetic Algorithm is applied to the problem of bottom recognition with synthetic noise-free acoustic data. The data correspond to three classes of benchmark problems. Four alternative objective functions have been tested, all of them defined to be used with broadband data with either coherent or incoherent processing in the frequency domain. It has been concluded that the parameters corresponding to the sediment layer and especially the sound speed, are more accurately recovered by all means. Source localization and water depth estimation are made with good accuracy in all cases. It has also been shown that incoherent processing in the frequency domain has led to better results for the cases studied.