Understanding deep-water striation patterns and predicting the waveguide invariant as a distribution depending on range and depth

The Waveguide Invariant (WI) theory has been introduced to quantify the orientation of the intensity interference patterns in a range-frequency domain. When the sound speed is constant over the water column, the WI is a scalar with the canonical value of 1. But, when considering shallow waters with a stratified sound speed profile, the WI ceases to be constant and is more appropriately described by a distribution, which is mainly sensitive to source/receiver depths. Such configurations have been widely investigated, with practical applications including passive source localization. However, in deep waters, the interference pattern is much more complex and variable. In fact the observed WI varies with source/receiver depth but it also varies very quickly with source-array range. In this paper, the authors investigate two phenomena responsible for this variability, namely the dominance of the acoustic field by groups of modes and the frequency dependence of the eigenmodes. Using a ray-mode approach, these two features are integrated in a WI distribution derivation. Their importance in deep-water is validated by testing the calculated WI distribution against a reference distribution directly measured on synthetic data. The proposed WI derivation provides a thorough way to predict and understand the striation patterns in deep-water context.

Geoacoustic inversion on the New England Mud Patch using warping and dispersion curves of high-order modes

This paper presents single receiver geoacoustic inversion of a combustive sound source signal, recorded during the 2017 Seabed Characterization Experiment on the New England Mud Patch, in an area where water depth is around 70 m. There are two important features in this study. First, it is shown that high-order modes can be resolved and estimated using warping (up to mode number 18 over the frequency band 20-440 Hz). However, it is not possible to determine mode numbers from the data, so that classical inversion methods that require mode identification cannot be applied. To solve this issue, an inversion algorithm that jointly estimates geoacoustic properties and identifies mode number is proposed. It is successfully applied on a range-dependent track, and provides a reliable range-average estimation of geoacoustic properties of the mud layer, an important feature of the seabed on the experimental area.

Using the trapped energy ratio for source depth discrimination with a horizontal line array: Theory and experimental results

The problem of acoustic source depth discrimination was introduced as a way to get basic information on source depth in configurations where accurate depth estimation is not feasible. It is a binary classification problem, aiming to evaluate whether the source is near the surface or submerged. Herein, the classification relies on a signal measured with a horizontal line array in shallow water. Knowing the source-array distance is not required but the source bearing has to be close to the array endfire. Signal processing relies on a normal-mode propagation model, and thus requires prior knowledge of the mode characteristics. The decision relies on an estimation of the trapped energy ratio in mode space. The performance is predicted with simulations and Monte Carlo methods, allowing one to compare several estimators based on different mode filters, and to choose an appropriate decision threshold. The impact on performance of frequency, noise level, horizontal aperture, and environmental mismatch is numerically studied. Finally, the approach is validated on experimental data acquired with a horizontal line array deployed off the coast of New Jersey, and the impact of errors in the environmental model is illustrated. The investigated approach successfully identifies a surface ship and a submerged towed source.

Identification of two potential whale calls in the southern Indian Ocean, and their geographic and seasonal occurrence

Since passive acoustic monitoring is widely used, unidentified acoustic signals from marine mammals are commonly reported. The signal characteristics and emission patterns are the main clues to identify the possible sources. In this study, the authors describe two previously unidentified sounds, recorded at up to five widely-spaced sites (30 × 30 degree area) in the southern Indian Ocean, in 2007 and between 2010 and 2015. The first reported signal (M-call) consists of a single tonal unit near 22 Hz and lasting about 10 s, repeated with an interval longer than 2 min. This signal is only detected in 2007. The second signal (P-call) is also a tonal unit of 10 s, repeated every 160 s, but at a frequency near 27 Hz. Its yearly number increased greatly between 2007 and 2010, and moderately since then. Based on their characteristics and seasonal patterns, this study shows that both signals are clearly distinct from any known calls of blue whale subspecies and populations dwelling in the southern Indian Ocean. However, they display similarities with blue whale vocalizations. More particularly, the P-call can be mistaken for the first tonal unit of the Antarctic blue whale Z-call.

Using nonlinear time warping to estimate North Pacific right whale calling depths in the Bering Sea

Calling depth distributions are estimated for two types of calls produced by critically endangered eastern North Pacific right whales (NPRWs) in the Bering Sea, using passive acoustic data collected with bottom-mounted hydrophone recorders. Nonlinear time resampling of 12 NPRW "upcalls" and 20 "gunshots" recorded in a critical NPRW habitat isolated individual normal mode arrivals from each call. The relative modal arrival times permitted range estimates between 1 and 40 km, while the relative modal amplitudes permitted call depth estimates, provided that environmental inversions were obtained from high signal-to-noise ratio calls. Gunshot sounds were generally only produced at a few meters depth, while upcall depths clustered between 10 and 25 m, consistent with previously published bioacoustic tagging results from North Atlantic right whales. A Wilcoxon rank sum test rejected the null hypothesis that the mean calling depths of the two call types were the same (p = 2.9 × 10^-5); the null hypothesis was still rejected if the sample set was restricted to one call per acoustic encounter (p = 0.02). Propagation modeling demonstrates that deeper depths enhance acoustic propagation and that source depth estimates impact both NPRW upcall source level and detection range estimates.

Waveguide mode amplitude estimation using warping and phase compensation

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.

Acoustic measurements of post-dive cardiac responses in southern elephant seals (Mirounga leonina) during surfacing at sea

Measuring physiological data in free-ranging marine mammals remains challenging, owing to their far-ranging foraging habitat. Yet, it is important to understand how these divers recover from effort expended underwater, as marine mammals can perform deep and recurrent dives. Among them, southern elephant seals (Mirounga leonina) are one of the most extreme divers, diving continuously at great depth and for long duration while travelling over large distances within the Southern Ocean. To determine how they manage post-dive recovery, we deployed hydrophones on four post-breeding female southern elephant seals. Cardiac data were extracted from sound recordings when the animal was at the surface, breathing. Mean heart rate at the surface was 102.4±4.9 beats min^-1 and seals spent on average 121±20 s breathing. During these surface intervals, the instantaneous heart rate increased with time. Elephant seals are assumed to drastically slow their heart rate (bradycardia) while they are deep underwater, and increase it (tachycardia) during the ascent towards the surface. Our finding suggests that tachycardia continues while the animal stays breathing at the surface. Also, the measured mean heart rate at the surface was unrelated to the duration and swimming effort of the dive prior to the surface interval. Recovery (at the surface) after physical effort (underwater) appears to be related to the overall number of heart beats performed at the surface, and therefore total surface duration. Southern elephant seals recover from dives by adjusting the time spent at the surface rather than their heart rate.

Seasonal and Diel Vocalization Patterns of Antarctic Blue Whale (Balaenoptera musculus intermedia) in the Southern Indian Ocean: A Multi-Year and Multi-Site Study

Passive acoustic monitoring is an efficient way to provide insights on the ecology of large whales. This approach allows for long-term and species-specific monitoring over large areas. In this study, we examined six years (2010 to 2015) of continuous acoustic recordings at up to seven different locations in the Central and Southern Indian Basin to assess the peak periods of presence, seasonality and migration movements of Antarctic blue whales (Balaenoptera musculus intermedia). An automated method is used to detect the Antarctic blue whale stereotyped call, known as Z-call. Detection results are analyzed in terms of distribution, seasonal presence and diel pattern of emission at each site. Z-calls are detected year-round at each site, except for one located in the equatorial Indian Ocean, and display highly seasonal distribution. This seasonality is stable across years for every site, but varies between sites. Z-calls are mainly detected during autumn and spring at the subantarctic locations, suggesting that these sites are on the Antarctic blue whale migration routes, and mostly during winter at the subtropical sites. In addition to these seasonal trends, there is a significant diel pattern in Z-call emission, with more Z-calls in daytime than in nighttime. This diel pattern may be related to the blue whale feeding ecology.

Source depth discrimination with a vertical line array

Source depth estimation with a vertical line array generally involves mode filtering, then matched-mode processing. Because mode filtering is an ill-posed problem if the water column is not well-sampled, concerns for robustness motivate a simpler approach: source depth discrimination considered as a binary classification problem. It aims to evaluate whether the source is near the surface or submerged. These two hypotheses are formulated in terms of normal modes, using the concept of trapped and free modes. Decision metrics based on classic mode filters are proposed. Monte Carlo methods are used to predict performance and set the parameters of a classifier accordingly.

Bayesian source localization with uncertain Green's function in an uncertain shallow water ocean

Matched-field acoustic source localization is a challenging task when environmental properties of the oceanic waveguide are not precisely known. Errors in the assumed environment (mismatch) can cause severe degradations in localization performance. This paper develops a Bayesian approach to improve robustness to environmental mismatch by considering the waveguide Green's function to be an uncertain random vector whose probability density accounts for environmental uncertainty. The posterior probability density is integrated over the Green's function probability density to obtain a joint marginal probability distribution for source range and depth, accounting for environmental uncertainty and quantifying localization uncertainty. Because brute-force integration in high dimensions can be costly, an efficient method is developed in which the multi-dimensional Green's function integration is approximated by one-dimensional integration over a suitably defined correlation measure. An approach to approximate the Green's function covariance matrix, which represents the environmental mismatch, is developed based on modal analysis. Examples are presented to illustrate the method and Monte-Carlo simulations are carried out to evaluate its performance relative to other methods. The proposed method gives efficient, reliable source localization and uncertainties with improved robustness toward environmental mismatch.

Automated detection of Antarctic blue whale calls

This paper addresses the problem of automated detection of Z-calls emitted by Antarctic blue whales (B. m. intermedia). The proposed solution is based on a subspace detector of sigmoidal-frequency signals with unknown time-varying amplitude. This detection strategy takes into account frequency variations of blue whale calls as well as the presence of other transient sounds that can interfere with Z-calls (such as airguns or other whale calls). The proposed method has been tested on more than 105 h of acoustic data containing about 2200 Z-calls (as found by an experienced human operator). This method is shown to have a correct-detection rate of up to more than 15% better than the extensible bioacoustic tool package, a spectrogram-based correlation detector commonly used to study blue whales. Because the proposed method relies on subspace detection, it does not suffer from some drawbacks of correlation-based detectors. In particular, it does not require the choice of an a priori fixed and subjective template. The analytic expression of the detection performance is also derived, which provides crucial information for higher level analyses such as animal density estimation from acoustic data. Finally, the detection threshold automatically adapts to the soundscape in order not to violate a user-specified false alarm rate.

Passive acoustic observations of tide height in the Iroise Sea using ambient noise

Considering a broadband motionless source in a waveguide with a depth that varies with time, the time-frequency representation of the acoustic intensity shows a striation pattern than can be explained using the depth-frequency waveguide invariant. This phenomenon is used here to describe acoustic data recorded in the Iroise Sea, where intense tides occur. The originality of this study is that the acoustic data consist of only ambient noise. The best hypothesis is that these striations are created by distant marine traffic in the Bay of Brest, and the results suggest that tide height can be monitored using long-term passive acoustics.

Compressed sensing for wideband wavenumber tracking in dispersive shallow water

In shallow water zones and at low frequency, seabed and water column properties can be estimated from the acoustic wavenumbers using inversion algorithms. When considering horizontal line arrays (HLA) and narrowband sources, the wavenumbers can be evaluated with classic spectral analysis methods. In this paper, a compressed sensing (CS) method for sparse recovery of the wavenumbers is proposed. This takes advantage of the few propagating modes and allows for spectral estimation when short HLA are used. The CS representation improves the wavenumber estimation, compared to the Fourier transform. However, for small arrays and several propagating modes, the CS generates interferences and does not allow proper wavenumber estimation. When considering broadband sources, it is possible to combine the wavenumbers estimated at several frequencies in order to build a frequency-wavenumber (f - k) representation. In this case, a post-processing tracking operation which improves the f - k resolution is presented. This relies on a general approach of waveguide physics and uses a particle filtering (PF) algorithm to track the wavenumbers. The consecutive use of CS and PF leads to a better wavenumber estimation. This methodology can be used for sources that are not at an end-fire position. It is illustrated by simulations and successfully applied on the Shallow Water 2006 data using the 32 sensor SHARK array.

Range estimation of bowhead whale (Balaena mysticetus) calls in the Arctic using a single hydrophone

Bowhead whales generate low-frequency calls in shallow-water Arctic environments, whose dispersive propagation characteristics are well modeled by normal mode theory. As each mode propagates with a different group speed, a call's range can be inferred by the relative time-frequency dispersion of the modal arrivals. Traditionally, at close ranges modal arrivals are separated using synchronized hydrophone arrays. Here a nonlinear signal processing method called "warping" is used to filter the modes on just a single hydrophone. The filtering works even at relatively short source ranges, where distinct modal arrivals are not separable in a conventional spectrogram. However, this warping technique is limited to signals with monotonically increasing or decreasing frequency modulations, a relatively common situation for bowhead calls. Once modal arrivals have been separated, the source range can be estimated using conventional modal dispersion techniques, with the original source signal structure being recovered as a by-product. Twelve bowhead whale vocalizations recorded near Kaktovik (Alaska) in 2010, with signal-to-noise ratios between 6 and 23 dB, are analyzed, and the resulting single-receiver range estimates are consistent with those obtained independently via triangulation from widely-distributed vector sensor arrays. Geoacoustic inversions for each call are necessary in order to obtain the correct ranges.

Autoregressive model for high-resolution wavenumber estimation in a shallow water environment using a broadband source

In a shallow water environment, wavenumbers can be estimated by computing time and spatial Fourier transforms of horizontal array measurements. The frequency-wavenumber representation allows wide band estimation but a sufficient number of hydrophones are required for accurate wavenumber resolution. This paper presents the application of an autoregressive (AR) model to compute the high resolution wavenumber spectrum. The smallest number of required sensors for the AR model is found using a stabilization diagram. The method is validated on simulated and experimental data. The wavenumbers are accurately estimated over a wide frequency band using fewer sensors than are needed for the spatial Fourier Transform.

Inversion of seabed attenuation using time-warping of close range data

An inversion scheme based on time-warping is presented for estimating seabed sound attenuation from modal dispersion of close-range single-hydrophone data. The dispersion information is extracted directly from the warped signal spectrum. Seabed sound speed and density are inverted from the modal group velocity curves, and the attenuation is inverted from the normalized modal amplitudes. The method is applied to experimental data collected in the Yellow Sea of China during the winter of 2002. The inverted sound speed and density are consistent with the sand-silt-clay sediment at the site, and the attenuation is nonlinear over the frequency band from 125-500 Hz.

Passive estimation of the waveguide invariant per pair of modes

In many oceanic waveguides, acoustic propagation is characterized by a parameter called waveguide invariant. This property is used in many passive and active sonar applications where knowledge of the waveguide invariant value is required. The waveguide invariant is classically considered as scalar but several studies show that it is better modeled by a distribution because of its dependence on frequency and mode pairs. This paper presents a new method for estimating the waveguide invariant distribution. Using the noise radiated by a distant ship and a single hydrophone, the proposed methodology allows estimating the waveguide invariant for each pair of modes in shallow water. Performance is evaluated on simulated data.

Bayesian geoacoustic inversion of single hydrophone light bulb data using warping dispersion analysis

This paper presents geoacoustic inversion of a light bulb implosion recorded during the Shallow Water 2006 experiment. The source is low frequency and impulsive, the environment is shallow water, and the acoustic signal is recorded using a single receiver. In this context, propagation is described by modal theory, and inversion is carried out by matching modal dispersion curves in the time-frequency domain. Experimental dispersion curves are estimated using an advanced signal processing method called warping, allowing inversion to be carried out at a relatively short range (~/=7 km). Moreover, the inversion itself is performed using Bayesian methodology. This allows inference of the seabed structure from the data, including the number of seabed layers resolved, optimal estimates of the seabed parameters, and quantitative uncertainty estimates. Inversion results of the experimental data are in good agreement with both ground truth and estimates from other experimental data in the same region.

Passive geoacoustic inversion with a single hydrophone using broadband ship noise

An inversion scheme is proposed, relying upon the inversion of the noise of a moving ship measured on a single distant hydrophone. The spectrogram of the measurements exhibits striations which depend on waveguide parameters. The periodic behavior of striations versus range are used to estimate the differences of radial wavenumber between couples of propagative modes at a given frequency. These wavenumber differences are stacked for several frequencies to form the relative dispersion curves. Such relative dispersion curves can be synthesized using a propagation model feeded with a bottom geoacoustic model. Inversion is performed by looking for the bottom properties that optimize the fit between measured and predicted relative dispersion curves. The inversion scheme is tested on simulated data. The conclusions are twofold: (1) a minimum 6 dB signal to noise ratio is required to obtained an unbiased estimate of compressional sound speed in the bottom with a 3 m s(-1) standard deviation; however, even with low signal to noise ratio, the estimation error remains bounded and (2) in the case of a multi-layer bottom, the scheme produces a single depth-average compressional sound speed. The inversion scheme is applied on experimental data. The results are fully consistent with a core sample measured around the receiving hydrophone.

Single-receiver geoacoustic inversion using modal reversal

This paper introduces a single-receiver geoacoustic-inversion method based on dispersion analysis and adapted to low-frequency impulsive sources in shallow-water environments. In this context, most existing methods take advantage of the modal dispersion curves in the time-frequency domain. Inversion is usually performed by matching estimated dispersion curves with simulated replicas. The method proposed here is different. It considers the received modes in the frequency domain. The modes are transformed using an operator called modal reversal, which is parameterized using environmental parameters. When modal reversal is applied using parameters that match the real environment, dispersion is compensated for in all of the modes. In this case, the reversed modes are in phase and add up constructively, which is not the case when modal reversal is ill-parameterized. To use this phenomenon, a criterion that adds up the reversed modes has been defined. The geoacoustic inversion is finally performed by maximizing this criterion. The proposed method is benchmarked against simulated data, and it is applied to experimental data recorded during the Shallow Water 2006 experiment.

Geoacoustic inversion in a dispersive waveguide using warping operators

This paper presents a single receiver geoacoustic inversion method adapted for low-frequency impulsive sources. It is applied to light bulb data collected during the Shallow Water 2006 experiment. The inversion is carried out by extracting dispersion curves from the received signal, and comparing them to simulated replicas. To achieve dispersion curve estimation in the time-frequency domain, modal separability is improved using a signal processing method called warping. The inversion scheme allows for a reliable estimation of the New Jersey Shelf sediment properties (compressional sound speed and density). It also provides an accurate estimation of the source/receiver range.

Modal depth function estimation using time-frequency analysis

Acoustic propagation in shallow water is characterized by a set of depth-dependent modes, the modal depth functions, which propagate in range according to their horizontal wavenumbers. For inversion purposes, modal depth function estimation in shallow water is an issue when the environment is not known. Classical methods that provide blind mode estimation rely on the singular value decomposition of the received field at different frequencies over a vertical array of transducers. These methods require that the vertical array spans the full water column. This is obviously a strong limitation for the application of such methods in an operational context. To overcome these shortcomings, this study proposes to replace the spatial diversity constraint by a frequency diversity condition, and thus considers the case of a field emanating from an impulsive source. Indeed, because of the discrete nature of the wavenumber spectrum and due to their dispersive behavior, the modes are separated in the time-frequency domain. This phenomenon enables the design of a modal filtering scheme for signals received on a single receiver. In the case of a vertical receiver array, the modal contributions can be isolated for each receiver even when using a partial water column spanning array. This method thus eliminates the receiving constraints of classical methods of modal depth function estimation, although it imposes the use of an impulsive source. The developed algorithm is benchmarked on numerical simulations and validated on laboratory experimental data recorded in an ultrasonic waveguide. Practical applications are also discussed.

Estimation of modal group velocities with a single receiver for geoacoustic inversion in shallow water

Due to the expense associated with at-sea sensor deployments, a challenge in underwater acoustics has been to develop methods requiring a minimal number of sensors. This paper introduces an adaptive time-frequency signal processing method designed for application to a single source-receiver sensor pair. The method involves the application of conjugate time-frequency warping transforms to improve the SNR and resolution of the time-frequency distribution (TFD) of the measured field. Such refined knowledge of the TFD facilitates efforts to extract tomographic information about the propagation medium. Here the method is applied to the case of modal propagation in a shallow ocean range independent environment to extract a refined TFD. Given knowledge of the source-receiver separation, the refined TFD is used to extract the frequency dependent group velocities of the individual modal components. The extracted group velocities are then incorporated into a computationally light tomographic inversion method. Simulated and experimental results are discussed.