Using Ocean Ambient Noise for Array Self-Localization and Self-Synchronization

Sabra, Karim G.; Roux, Philippe; Thode, Aaron; D’Spain, Gerald L.; Hodgkiss, William S.; Kuperman, W. A.

doi:10.1109/joe.2005.850908

Cited by 110 publications

(69 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, previous studies have established that the N · M pairs of coherent arrivals extracted between the two hydrophone arrays, each containing a different number of elements N and M, respectively, can be jointly processed (via the beamforming procedure used in this study) to provide arrival time variations from passive thermometry with an associated measurement error inversely proportional ffiffiffiffiffiffiffi ffi T=L p Á ffiffiffiffiffiffiffi MN p Sabra et al, 2005bSabra et al, , 2005cLeroy et al, 2012], where L is the separation distance between the centers of the two receiver arrays. Note that this simple scaling argument assumes that the statistics and generation mechanism of the Polar noise sources driving the longer range results would remain comparable to those used in this study.…”

Section: 1002/2015gl063438mentioning

confidence: 99%

Monitoring deep‐ocean temperatures using acoustic ambient noise

Woolfe

Lani

Sabra

et al. 2015

Geophysical Research Letters

View full text Add to dashboard Cite

Measuring temperature changes of the deep oceans, important for determining the oceanic heat content and its impact on the Earth's climate evolution, is typically done using free‐drifting profiling oceanographic floats with limited global coverage. Acoustic thermometry provides an alternative and complementary remote sensing methodology for monitoring fine temperature variations of the deep ocean over long distances between a few underwater sources and receivers. We demonstrate a simpler, totally passive (i.e., without deploying any active sources) modality for acoustic thermometry of the deep oceans (for depths of ~ 500–1500 m), using only ambient noise recorded by two existing hydroacoustic stations of the International Monitoring System. We suggest that passive acoustic thermometry could improve global monitoring of deep‐ocean temperature variations through implementation using a global network of hydrophone arrays.

show abstract

Section: 1002/2015gl063438mentioning

confidence: 99%

Monitoring deep‐ocean temperatures using acoustic ambient noise

Woolfe

Lani

Sabra

et al. 2015

Geophysical Research Letters

View full text Add to dashboard Cite

show abstract

“…The better the estimate of the GF, the better the estimate in the passive fathometer. Two figures of merit for the estimates of the GF are the SNR and the resolution of the Cross-Correlation Function (CCF) [7,[9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Another way of collecting large amounts of data is to use an array of hydrophones. In array processing, signals from different pairs of hydrophone are averaged together to improve the SNR of the correlation function [1, 2,9]. The number of elements of the array can be increased to increase the SNR of the correlation function [2,5,10], but the array becomes physically larger.…”

Section: Introductionmentioning

confidence: 99%

“…That is, due to spatial aliasing the bandwidth cannot be larger than the design frequency of the array [2], even though the SNR and resolution can be improved by the increase of the bandwidth [9][10][11]17]. Some recent works show that the bandwidth can be increased by up to twice the design frequency without affecting the performance as a conesquence of spatial aliasing [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effect of Biological Activity on Broadband Passive Fathometry

Alam¹,

Huntington²,

Frater³

2013

OJA

View full text Add to dashboard Cite

A passive fathometer can be formed by two vertically separated hydrophones. The depth can be estimated from the Green's function between the hydrophones, which is calculated from the cross-correlation between ocean ambient noise fields received at those two hydrophones. The performance of the fathometer depends on the signal to noise ratio (SNR) and the resolution of the noise cross-correlation function. In a given environment, improved SNR and resolution of the cross-correlation function can be achieved through longer observations, more observation points, or increasing bandwidth. Long time averaging has been demonstrated, but requires that the channel be stationary over the averaging time. Hydrophone arrays are commonly used, but result in increased cost and complexity. Recent work shows that the SNR and resolution of the correlation function can also be improved by the use of the large bandwidth noise fields. This paper shows that the non-surface biological noise generated by marine animals, such as shrimp, is one of the major issues in the performance of such a broadband passive fathometer operating in shallow water. This noise tends to occur at higher frequencies. Frequencies at which significant non-surface biological noise is present cannot be used to improve fathometer performance. Consequently, the upper limit of frequencies that can be used in a passive fathometer is limited by the lower limit of the bandwidth occupied by the biological noise.

show abstract

“…If the wave dynamics is time reversal symmetric, the correlation admits also a symmetry by changing τ into −τ ; this observation has been used for clock synchronisation, see [22].…”

Section: Introductionmentioning

confidence: 99%

Semiclassical analysis and passive imaging

Verdìère

2009

Nonlinearity

View full text Add to dashboard Cite

The propagation of elastic waves inside the Earth provides us with informations about the geological structure of the Earth's interior. Since the beginning of seismology, people have been using waves created by earthquakes or by artificial explosions. They record the waves as functions of time using seismometers located at different stations on the Earth's surface. Even without any earthquake or explosion, a weak signal is still recorded which has no evident structure: it is a "noise". How to use these noises? This is the goal of the method of "passive imaging". The main observation is the following one: the time correlation of the noisy fields, computed from the fields recorded at the points A and B, is "close" to the Green's function G(τ, A, B) of the wave propagation. The aim of this paper is to provide a mathematical context for this approach and to show, in particular, how the methods of semiclassical analysis can be be used in order to find the asymptotic behaviour of the correlations.

show abstract

Using Ocean Ambient Noise for Array Self-Localization and Self-Synchronization

Cited by 110 publications

References 19 publications

Monitoring deep‐ocean temperatures using acoustic ambient noise

Monitoring deep‐ocean temperatures using acoustic ambient noise

Effect of Biological Activity on Broadband Passive Fathometry

Semiclassical analysis and passive imaging

Contact Info

Product

Resources

About