Measuring the effect of ambient noise directionality and split-beam processing on the convergence of the cross-correlation function

Abstract

Measurements of ambient noise have been used to infer information about the ocean acoustic environment. In recent years the correlation of ambient noise has been shown to give estimates of the travel time of acoustic paths between the sensors recording the noise. A number of issues affect the results of the noise correlation. This paper presents the results of noise correlation of the two horizontally separated arrays of sensors in the 2010 ambient noise experiment. Using the experimental data, the effects on the convergence of the noise correlation are examined with respect to the size and shape of the arrays, the length of time used, and the directionality of the noise field.

Acoustic Green's function extraction from ambient noise in a coastal ocean environment

“…These arguments suggest that conditions for noise interferometry are at least as favorable at r = 50 km, h = 5km as under conditions that we have reported on. Also, we note that, independent of water depth and details of propagation conditions, better results (e.g., shorter required coherent stacking time to extract Green's function estimates with adequate signal‐to‐noise ratio) are expected [ Burov et al , ; Leroy et al , ; Menon et al , ; Goncharov et al , ; Fried et al , ] if point measurements are replaced by vertical array measurements, even short arrays. With these comments in mind, we are optimistic about the potential of using noise interferometry as the basis for tomographic inversions at ranges longer than those considered in this letter.…”

“…Passive fathometer applications are a special case, corresponding to effectively 1-D (vertical) propagation, which have proven to be successful [Siderius et al, 2006[Siderius et al, , 2010Gerstoft et al, 2008]. There have also been several successful demonstrations at horizontal separations ranging from a few hundred meters [Fried et al, 2008;Brooks and Gerstoft, 2009;Fried et al, 2013;Lani et al, 2013] to 3.5 km [Roux et al, 2004;Sabra et al, 2013]. Additionally, Godin et al [2010] have successfully demonstrated the feasibility of passive acoustic tomography by retreiving the sound speed from moored mid-ocean noise measurements with horizontal separations of 0.5 to 3.5 km.…”

Monitoring deep‐ocean temperatures using acoustic ambient noise

“…The generation mechanism and propagation paths of the ambient noise toward hydroacoustic stations affect the peak-to-variance ratio for the coherent arrivals extracted from this noise correlation processing [Roux et al, 2004;Godin et al, 2010;Fried et al, 2013]. Hence, we first characterized the predominant noise sources and spatial origin of the ambient noise components used in this study.…”

“…For instance, ambient noise correlation processing has successfully been used to continuously monitor with unprecedented temporal resolution seismically active systems such as fault zones [Brenguier et al, 2008] and volcanic areas [Brenguier et al, 2014]. In the context of ocean acoustics [Roux et al, 2004;Godin et al, 2010;Fried et al, 2013;Brown et al, 2014], previous studies have demonstrated that the noise correlation method requires excessively long integration (i.e., averaging) times to reliably estimate the same discrete slanted acoustic paths used to infer temperature variations by previous acoustic thermometry studies conducted with active sources [The ATOC Consortium, 1998;Munk et al, 1995]. Consequently, since this integration time is typically too long compared to the time scale of ocean fluctuations, this would prevent the application of the ambient noise correlation processing technique for acoustic thermometry purposes if those discrete slanted acoustic paths were to be selected [Roux et al, 2004;Godin et al, 2010;Fried et al, 2013;Brown et al, 2014].…”

“…In the context of ocean acoustics [Roux et al, 2004;Godin et al, 2010;Fried et al, 2013;Brown et al, 2014], previous studies have demonstrated that the noise correlation method requires excessively long integration (i.e., averaging) times to reliably estimate the same discrete slanted acoustic paths used to infer temperature variations by previous acoustic thermometry studies conducted with active sources [The ATOC Consortium, 1998;Munk et al, 1995]. Consequently, since this integration time is typically too long compared to the time scale of ocean fluctuations, this would prevent the application of the ambient noise correlation processing technique for acoustic thermometry purposes if those discrete slanted acoustic paths were to be selected [Roux et al, 2004;Godin et al, 2010;Fried et al, 2013;Brown et al, 2014]. However, for deep-ocean propagation, there is an unusually stable acoustic feature-the last and most energetic arrival corresponding to sound propagating nearly horizontally along the Sound Fixing and Ranging (SOFAR) channel-which can thus be estimated using ambient noise correlations computed over a finite integration time.…”