Sediment sound speed inversion with time-frequency analysis and modal arrival time probability density functions

Abstract

The dispersion pattern of a received signal is critical for understanding physical properties of the propagation medium. The objective of this work is to estimate accurately sediment sound speed using modal arrival times obtained from dispersion curves extracted via time-frequency analysis of acoustic signals. A particle filter is used that estimates probability density functions of modal frequencies arriving at specific times. Employing this information, probability density functions of arrival times for modal frequencies are constructed. Samples of arrival time differences are then obtained and are propagated backwards through an inverse acoustic model. As a result, probability density functions of sediment sound speed are estimated. Maximum a posteriori estimates indicate that inversion is successful. It is also demonstrated that multiple frequency processing offers an advantage over inversion at a single frequency, producing results with reduced variance.

Nonlinear time-warping made simple: A step-by-step tutorial on underwater acoustic modal separation with a single hydrophone

“…Such a situation is classical in the Arctic during summer but also happens at lower latitudes under specific oceanographic conditions. Spectrograms of experimental data with this specific features can be found in (Michalopoulou and Pole, 2016) or (Roth et al, 2012). Last but not least, this tutorial is based on the underlying assumption that the signal under study is a transient signal (such as an impulse or a frequency-modulated sweep) recorded on a single hydrophone.…”

Environmental inversion using dispersion tracking in a shallow water environment

“…For the dynamic acoustic model, transforming the PDF of arrival times of distinct frequencies into a PDF of arrival time differences is described in Ref. 8. For the normal modes model, the procedure is to work with each three-dimensional parameter grid point: (i) compute group velocities for frequencies; (ii) combine the group velocities with the known source-receiver distance to obtain modal arrival times for frequencies; (iii) hence, compute the arrival time differences.…”

“…[1][2][3][4][5][6][7][8] A technique was recently suggested for inverting for the sediment sound speed from dispersion curves extracted from synthetic data. 7,8 The approach is extended here in two ways: we demonstrate that inversion for (1) multiple parameters is feasible from (2) real data generated by the Gulf of Mexico experiment.…”

“…The first step is to slice the time series into a series of windows and compute the Fourier transform (FT) on each, providing the Short Term Fourier Transform (STFT) of the signal. From this transform and using particle filtering, [7][8][9][10][11][12][13] we extract the probability density function (PDF) of the modal frequencies at each time.…”

“…The PDFs of arrival time differences are then obtained directly. 8 The third step is to propagate the arrival time differences through the inverse model to calculate the PDFs of the environmental/geoacoustic parameters.…”