Bayesian geoacoustic inversion using wind-driven ambient noise

Abstract

This paper applies Bayesian inversion to bottom-loss data derived from wind-driven ambient noise measurements from a vertical line array to quantify the information content constraining seabed geoacoustic parameters. The inversion utilizes a previously proposed ray-based representation of the ambient noise field as a forward model for fast computations of bottom loss data for a layered seabed. This model considers the effect of the array's finite aperture in the estimation of bottom loss and is extended to include the wind speed as the driving mechanism for the ambient noise field. The strength of this field relative to other unwanted noise mechanisms defines a signal-to-noise ratio, which is included in the inversion as a frequency-dependent parameter. The wind speed is found to have a strong impact on the resolution of seabed geoacoustic parameters as quantified by marginal probability distributions from Bayesian inversion of simulated data. The inversion method is also applied to experimental data collected at a moored vertical array during the MAPEX 2000 experiment, and the results are compared to those from previous active-source inversions and to core measurements at a nearby site.

Synthetic array processing of ocean ambient noise for higher resolution seabed bottom loss estimation

“…The seabed has a 0.75 m layer over a half-space. The layer has sound speed of 1550 m/s, density of 1.5 g/cm 3 , and attenuation of 0.2 dB/wavelength. The infinite halfspace below has sound speed of 1600 m/s, density of 2.0 g/cm 3 , and attenuation of 0.15 dB/wavelength.…”

“…The layer has sound speed of 1550 m/s, density of 1.5 g/cm 3 , and attenuation of 0.2 dB/wavelength. The infinite halfspace below has sound speed of 1600 m/s, density of 2.0 g/cm 3 , and attenuation of 0.15 dB/wavelength. The 0.75 m layer gives rise to an interference in the bottom reflection loss, which is also apparent in the beamformer output.…”

“…It can also create errors if the estimated bottom loss is used in an inversion scheme to estimate geo-acoustic properties of the seabed. 2,3 In this paper, the Toeplitz (or approximately Toeplitz) property of the ambient noise cross-spectral-density matrix (CSDM) is used to reduce the degree of smearing caused by the finite beams. This property simply implies that the noise spatial coherence depends only on the distance between hydrophones and not their absolute position in the water column.…”

Trans-dimensional geoacoustic inversion of wind-driven ambient noise

“…The signal-tonoise ratio (SNR) parameters account for the strength of the wind-driven ambientnoise data (i.e., the useful signal) versus other unwanted sources of noise and are included as parameters to be estimated from the data at F frequencies. As in previous work, 7 the marginal PPD of SNRs corresponding to simulated data are centered around the true (known) values used to generate the simulated data (not shown). In the case of experimental data, the SNRs depend on unknown factors, 7 such as the frequency-dependent sensitivity of the array elements, sensor pre-amplifiers, and accuracy of the recording system.…”

“…From these passive techniques, inversion of wind-driven ambient noise recorded at a vertical linear array (VLA) requires only simple hardware and deployment procedures, it has minimal environmental impact, and its generating mechanism is ubiquitous in the ocean, 1,6,7 making this technique suitable for exploring large geographic areas. A compelling demonstration of the seabed layering information carried by ambient noise is the passive fathometer, 6 which has been shown to image seabed layering in terms of the time of arrival of acoustic reflections from sub-bottom layers.…”