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The study of the acoustic emission of underwater gas bubbles is a subject ofboth theoretical and applied interest, since it finds an important applicationin the development of acoustic monitoring tools for detection andquantification of underwater gas leakages. An underlying physical model isessential in the study of such emissions, but is not enough: also somestatistical procedure must be applied in order to deal with all uncertainties(including those caused by background noise). In this paper we take aprobabilistic (Bayesian) methodology which is well known in the statisticalsignal analysis communitiy, and apply it to the problem of estimating the radiiof air bubbles in water. We introduce the bubblegram, a feature extractiontechnique graphically similar to the traditional spectrogram but tailored torespond only to pulse structures that correspond to a given physical model. Weinvestigate the performance of the bubblegram and our model in general usinglaboratory generated data.

Estimating the radii of air bubbles in water using passive acoustic monitoring