Estimates of the temporal and spatial variability of ocean sound speed on the New Jersey shelf

Ballard, Megan S.; Frisk, George V.; Becker, Kyle M.

doi:10.1121/1.4875715

Cited by 22 publications

(10 citation statements)

References 36 publications

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“…Warping has notably been used for environmental estimation studies, mostly seabed geoacoustic inversion (Bonnel et al, 2013a;Bonnel et al, 2019;Bonnel et al, 2012;Dong et al, 2017;Duan et al, 2016;Feng-Hua et al, 2014;Petrov, 2014;Zeng et al, 2013), but also water column tomography (Ballard et al, 2014), as well as joint estimation of water column and seabed properties (Warner et al, 2015). On a more basic research point of view, it is interesting to note that warping has also been used to estimate modal depth functions Thode and Bonnel, 2015), as well as to filter modes from noise interferometry data (Sergeev et al, 2017;Tan et al, 2018).…”

Section: Warping In Ocean Acousticsmentioning

confidence: 99%

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

Bonnel

Thode

Wright

et al. 2020

The Journal of the Acoustical Society of America

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Classical ocean acoustic experiments involve the use of synchronized arrays of sensors. However, the need to cover large areas and/or the use of small robotic platforms has evoked interest in single-hydrophone processing methods for localizing a source or characterizing the propagation environment. One such processing method is “warping,” a non-linear, physics-based signal processing tool dedicated to decomposing multipath features of low-frequency transient signals (frequency f < 500 Hz), after their propagation through shallow water (depth D < 200 m) and their reception on a distant single hydrophone (range r > 1 km). Since its introduction to the underwater acoustics community in 2010, warping has been adopted in the ocean acoustics literature, mostly as a pre-processing method for single receiver geoacoustic inversion. Warping also has potential applications in other specialties, including bioacoustics; however, the technique can be daunting to many potential users unfamiliar with its intricacies. Consequently, this tutorial article covers basic warping theory, presents simulation examples, and provides practical experimental strategies. Accompanying supplementary material provides matlab code and simulated and experimental datasets for easy implementation of warping on both impulsive and frequency-modulated signals from both biotic and man-made sources. This combined material should provide interested readers with user-friendly resources for implementing warping methods into their own research.

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Section: Warping In Ocean Acousticsmentioning

confidence: 99%

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

Bonnel

Thode

Wright

et al. 2020

The Journal of the Acoustical Society of America

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“…Each frequency component of each mode travels with its own group speed, so that modal arrivals have frequency dependent travel times. Provided that these travel times can be estimated from the data, they can be used as input for inversion algorithms, to estimate source range [4]- [7], water sound-speed profile (SSP) [8], [9], and/or seabed geoacoustic properties [5], [9]- [12].…”

Section: Introductionmentioning

confidence: 99%

Trans-Dimensional Inversion of Modal Dispersion Data on the New England Mud Patch

Bonnel¹,

Dosso²,

Eleftherakis³

et al. 2020

IEEE J. Oceanic Eng.

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This paper presents single receiver geoacoustic inversion of two independent data sets recorded during the 2017 seabed characterization experiment on the New England Mud Patch. In the experimental area, the water depth is around 70 m, and the seabed is characterized by an upper layer of fine grained sediments with clay (i.e., mud). The first data set considered in this paper is a combustive sound source signal, and the second is a chirp emitted by a J15 source. These two data sets provide differing information on the geoacoustic properties of the seabed, as a result of their differing frequency content, and the dispersion properties of the environment. For both data sets, source/receiver range is about 7 km, and modal time-frequency dispersion curves are estimated using warping. Estimated dispersion curves are then used as input data for a Bayesian trans-dimensional inversion algorithm. Subbottom layering and geoacoustic parameters (sound speed and density) are thus inferred from the data. This paper highlights important properties of the mud, consistent with independent in situ measurements. It also demonstrates how information content differs for two data sets collected on reciprocal tracks, but with different acoustic sources and modal content. Index Terms-Geoacoustic inversion, New England mud patch, seabed characterization experiment (SBCEX), underwater acoustics, warping.

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“…The warping function that is (nearly) unanimously used in the ocean acoustics community derives from an ideal-isovelocity waveguide approximation. [14][15][16][17][18][19][20][21][22][23][24][25] The utility of such a model is that it provides a simple analytical warping solution that is applicable to every mode present in the signal. Other approximations exist that also permit warping every mode at once, e.g., approximated Pekeris waveguide, 13 waveguide invariant 26,27 or beam-displacement ray-mode theory.…”

Section: Introductionmentioning

confidence: 99%

“…Warping based on the ideal-isovelocity approximation, called "isovelocity warping" here, has been found to be robust to environmental mismatch, allowing successful modal filtering for real data in relatively complex shallow-water environments. It has been used by various researchers for numerous applications, including geoacoustic inversion, [15][16][17] water column tomography, 18 marine mammal localization, [19][20][21] etc. Nonetheless, modal filtering using isovelocity warping presents some limitations.…”

Section: Introductionmentioning

confidence: 99%

“…Modal filtering using isovelocity warping provides a reliable estimate of the mode phase; however, it seems to be less reliable for mode amplitude estimation, in particular, the first arriving mode. Indeed, for all the successful applications of warping previously cited, [14][15][16][17][18][19][20][21] the inversion algorithm was based on the modal phase (or, equivalently, on the modal TF dispersion curves that directly derives from the modal phase). On the other hand, very few at-sea applications have benefited from mode amplitude estimated using warping.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Waveguide mode amplitude estimation using warping and phase compensation

Bonnel

Caporale

Thode

2017

The Journal of the Acoustical Society of America

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In shallow water, low-frequency propagation can be described by modal theory. Acoustical oceanographic measurements under this situation have traditionally relied on spatially filtering signals with arrays of synchronized hydrophones. Recent work has demonstrated how a method called warping allows isolation of individual mode arrivals on a single hydrophone, a discovery that subsequently opened the door for practical single-receiver source localization and geoacoustic inversion applications. Warping is a non-linear resampling of the signal based on a simplistic waveguide model. Because warping is robust to environmental mismatch, it provides accurate estimates of the mode phase even when the environment is poorly known. However, the approach has issues with mode amplitude estimation, particularly for the first arriving mode. As warping is not invariant to time shifting, it relies on accurate estimates of the signal's time origin, which in turn heavily impacts the first mode's amplitude estimate. Here, a revised warping operator is proposed that incorporates as much prior environmental information as possible, and is actually equivalent to compensating the relative phase of each mode. Warping and phase compensation are applied to both simulated and experimental data. The proposed methods notably improve the amplitude estimates of the first arriving mode.

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Estimates of the temporal and spatial variability of ocean sound speed on the New Jersey shelf

Cited by 22 publications

References 36 publications

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

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

Trans-Dimensional Inversion of Modal Dispersion Data on the New England Mud Patch

Waveguide mode amplitude estimation using warping and phase compensation

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