Range-dependent Environments Research Articles

The effects of bathymetry on estimating the depth of a source in range-dependent environments with a single hydrophone

The effects of varying or range-dependent bathymetry, e.g., such as a sloping bottom, on the depth resolution characteristics of single hydrophone matched field processing (MFP), e.g., width of depth main-lobe as a function of source and receiver nominal positions, is not well understood. A major challenge is that in the case of range-dependent environments there are generally no analytical representations for the pressure field, thus requiring numerical methods for their evaluation. To provide some theoretical insights into how the shape of the bathymetry and locations of the source and receiver influences the MFP depth ambiguity function, we study the case of an ideal wedge with perfectly reflective pressure-release boundaries using the analytical solutions of Buckingham [1]. We derive a simple approximation for the depth ambiguity function main lobe width and compare it against the theoretical result for an ideal range-independent environment [2] and then numerically for a penetrable wedge and more realistic shelf-like environments. M.K. Buckingham, “Acoustic propagation in a wedge-shaped ocean with perfectly reflecting boundaries,” NRL report 8793, March 1984. M. Cheney and I.P. Kirsteins, “Resolution of matched field processing for a single hydrophone in a rigid waveguide,” J. Acoust Soc. Am. 151, pp. 3186–3197, 2022.

A study of range dependent acoustical field based on the FVCOM model: A Case of typhoon NANMADOL

This study simulated the acoustical field in the western North Pacific (WNP) during typhoon NANMADOL, based on the FVCOM model and Range dependent Acoustic Model RAM. We implements a new approach, which helps to accurately characterize the energy distribution of acoustical field obtained by considering the range dependent ocean dynamical environment elements. The results show that, the sound speed profile in the upper-layer ocean of the sea water decreases to a certain extent on the day after the typhoon’s arrival, while the maximum decrease in the sound speed after the typhoon’s transit occurs 1∼2 days. The maximum decrease in the seawater sound speed can be up to 2-3 m/s 2 days after the typhoon’s transit. The passage of the typhoon mainly affects the far-field acoustical energy distribution when the sound source is located near the upper-layer ocean.

Waveguide invariant navigation of an AUV with a towed line array

Passive acoustics navigation of an autonomous underwater vehicle (AUV) can reduce localization errors while being relatively low-cost. A promising approach for navigation in shallow water is to exploit the waveguide invariant, which makes it possible to estimate the range between an acoustic source with a known position and an acoustic receiver on the AUV. This range estimate can then be fused in a sequential Bayes framework to improve the navigation information of the AUV. While previously proposed methods consider a range-independent environment with a single acoustic source and a single receiver, we investigate a more realistic scenario with multiple sources in a potentially range-dependent environment. In particular, a shallow water environment with a constant slope and sound speed is considered. To resolve multiple sources, it is assumed that the AUV tows an acoustic line array. Simulated acoustic data provided by a normal mode program are used to study the feasibility of the AUV navigation in shallow water by exploiting the waveguide invariant in this setting.

Source depth estimation with feature matching using convolutional neural networks in shallow water

A feature matching method based on the convolutional neural network (named FM-CNN), inspired from matched-field processing (MFP), is proposed to estimate source depth in shallow water. The FM-CNN, trained on the acoustic field replicas of a single source generated by an acoustic propagation model in a range-independent environment, is used to estimate single and multiple source depths in range-independent and mildly range-dependent environments. The performance of the FM-CNN is compared to the conventional MFP method. Sensitivity analysis for the two methods is performed to study the impact of different environmental mismatches (i.e., bottom parameters, water column sound speed profile, and topography) on depth estimation performance in the East China Sea environment. Simulation results demonstrate that the FM-CNN is more robust to the environmental mismatch in both single and multiple source depth estimation than the conventional MFP. The proposed FM-CNN is validated by real data collected from four tracks in the East China Sea experiment. Experimental results demonstrate that the FM-CNN is capable of reliably estimating single and multiple source depths in complex environments, while MFP has a large failure probability due to the presence of strong sidelobes and wide mainlobes.

Modelling sound particle motion in shallow watera).

Fish species and aquatic invertebrates are sensitive to underwater sound particle motion. Studies on the impact of sound on marine life would benefit from sound particle motion models. Benchmark cases and solutions are proposed for the selection and verification of appropriate models. These include a range-independent environment, with and without shear in the sediment, and a range-dependent environment, without sediment shear. Analysis of the acoustic impedance illustrates that sound particle velocity can be directly estimated from the sound pressure field in shallow water scenarios, except at distances within one wavelength of the source, or a few water depths at frequencies where the wavelength exceeds the water depth.

Training a deep operator network as a surrogate solver for two-dimensional parabolic-equation models.

Parabolic equations (PEs) are useful for modeling sound propagation in a range-dependent environment. However, this approach entails approximating a leading-order cross-derivative term in the PE square-root operators. Deep operator networks (DeepONets) are designed to approximate operators. In this paper, we train DeepONets to take complex sound pressure and speed of sound at any depth location of interest as inputs and approximate the PE square operator in modeling two-dimensional sound propagation. Once trained, a network can predict the far field for a wide variety of environmental conditions, without needing to approximate the operator or calculate the whole mode trajectory and at a lower computational cost. The original DeepONet learns the operator of a single function. By contrast, the modified version presented here learns multiple-input operators with Fourier features. Using computational and theoretical examples, we demonstrate that DeepONet is efficient for learning complex ocean acoustic physics with good accuracy.

Application of trans-dimensional particle filtering for geoacustic inversion

The acquiring geoacoustic model and associated geoacoustic parameters is vital for sound propagation modelling in a range-dependent environment. Conventional sequential methods, e.g., particle filtering and Kalman filtering have been widely used for geoacoustic inversion in range-dependent environment, which encounter challenges when confronted with unknown geoacoustic models that intrinsically varying with range. As an attempt to estimate geoacoustic model and associated geoacoustic parameters as well, a trans-dimensional particle filtering method is presented here. This method integrates birth-death rules into the filtering process, enabling automatic selection of appropriate geoacoustic models and estimating geoacoustic parameters in the same time. Numerical simulations were conducted based on an environment model of the South China Sea, where a sea trial was conducted in 2022. Numerical results demonstrate the efficiency in accurately estimating the geoacoustic model variations and associated parameters. Preliminary results of sea trial data processing are also presented here.

Basin scale propagation modeling of MLS signals from the Kauai Beacon source

Long distance underwater acoustic propagation is of interest for a variety of applications including underwater navigation, yet modeling such propagation is challenging due to the large degree of environmental uncertainty. In this presentation, the propagation of 75Hz center frequency maximum length sequence (MLS) signals emitted from a submerged source near Kauai and received at various sites throughout the Pacific Ocean Basin is modeled with the Bellhop ray tracing [1] and Monterey-Newport Parabolic Equation [2] models. Sites such as the Monterey Accelerated Research System (MARS) observatory and the Comprehensive Nuclear Test Ban Organization (CTBTO) hydroacoustic monitoring station near Wake Island are included in the discussion. The range-dependent environment is based on historical profiles from the World Ocean Atlas database and reanalysis data from the hybrid coordinate ocean model (HYCOM) [3]. Bathymetry profiles along the axis of propagation are interpolated from the General Bathymetric Chart of the Oceans (GEBCO) 2021 database [4]. Simulated broadband channel impulse responses transmission loss levels in the modeled environment are compared to selected receptions of the signal at the hydrophone sites. Additionally, fluctuations of the modeled transmission loss in the presence of an internal wave model [5] are discussed.

Correction factors for loss estimation of sound propagation over high shear speed seabeds

Modelling range dependent sound propagation over layered elastic seafloors with high shear speeds has proved to be a difficult problem for many widely used under water acoustic sound propagation models. The geologic evolution of large portions of the Australian continental shelf result in it being a commonly occurring problem for sound propagation modelling. There has been success in developing numerical methods that have shown that it is possible to obtain accurate results for these types of range dependent environments; however, there may be issues with stability and efficiency. This article explores the appropriateness of correction factors to estimate the loss due to elastic seabeds with high shear speeds. The focus is on layered calcareous seafloors that are typical of the Otway shelf, located on the western flank of Bass Strait. Several methods for obtaining a dB correction that can be applied to a fluid only propagation model are presented and compared. The methods are validated against measurement data from an oil and gas campaigns in the Otway basin.

Correction: Skarsoulis et al. Prediction of Shipping Noise in Range-Dependent Environments. J. Mar. Sci. Eng. 2023, 11, 290

There was an error in the original publication [...]

ALMA 2022 experiment : Source paramater estimation comparison betweenLFM and MLS waveforms

For underwater source localization, accurate estimation of the time of flight (or travel time) is required and the observed waveform may include Doppler (waveform dilation). The source waveform, thus, needs to be sensitive to estimate both time of flight and Doppler. In this study, we compare two waveforms : Linear Frequency Modulated sweeps (LFMs) and Maximum Length Sequences (MLSs) with identical center frequency (6 kHz) and bandwidth (2 kHz). During an at-sea experiment conducted in March 2022 near in the Mediterranean Sea, near the coast of Toulon, a mobile source transmitted the two waveforms, recorded by a 192-hydrophone moored bilboard array. The source-array distance ranged from 2.5 to 8 km, and the source was towed at a constant speed (∼1.5 m/s) and depth (∼50m). The analysis of the gathered data shows that the MLS waveform outperforms the LFM waveform for estimating time of flight (uncertainty reduced by a factor 4) and radial velocity (uncertainty reduced by a factor 20). Preliminary results focus on single hydrophone processing, but possible applications to 2D array processing are discussed for localizing the source in range-dependent environments.

Prediction of Shipping Noise in Range-Dependent Environments

A prediction model for shipping noise in range-dependent environments based on coupled-mode theory is presented, as an enhancement to existing adiabatic normal-mode approaches without a significant increase in computational effort. Emphasis is placed on the categorization of environmental changes and precalculation and storage of eigenvalues, eigenfunctions and coupling matrices, such that they can be looked up and restored to efficiently compute the acoustic field of arbitrary noise source distributions over a given sea area. Taking into account that the water depth is the primary factor determining the number of propagating modes for a particular frequency, coupling is applied only in the case of changing bathymetry, whereas changes in the water sound-speed profile and/or the geoacoustic characteristics are treated adiabatically. Examples of noise calculations are given for benchmark setups in the Eastern Mediterranean Sea and comparisons with fully adiabatic predictions are drawn. Moreover, the effect of applying range propagation limitations in a numerical propagation model for shipping noise predictions is demonstrated.

Influence of Range-Dependent Sound Speed Profile on Position of Convergence Zones

Based on the Wentze–Kramers–Brillouin approximation, we derive formulae to calculate the position of convergence zones in a range-dependent environment with sound speed profiles varying in linear and ellipsoidal Gaussian eddy cases. Simulation results are provided for the linear and ellipsoidal Gaussian eddy cases. Experiment data are used for calculations considering linearly varying sound speed, and the findings suitably agree with the simulation results. According to the evaluated environment, the influence of the range-dependent sound speed profile on the position of the upper and lower convergence zones for different source depths is analyzed through simulations. The corresponding results show that the influence of the sound speed profile on the position of the upper convergence zone is greater for a shallower source. In contrast, the position of the lower convergence zone for large-depth reception is less affected.

Broadband acoustic wave propagation in temporally variable range dependent shallow water environment

Broadband acoustic wave propagation in shallow water regions involves interactions with the sea surface, sea bottom, and the water column. The topic of shallow water acoustics in the presence of variable water column has been of interest in recent years. Experimental observations have shown the importance of the effects due to the boundaries and the sound speed profile in the water column. However, more work needs to be done to establish ground truth in numerical modeling for temporally variable water column in a range dependent environment. In this paper we examine the broadband propagation on the shelf as well as the range dependent shelf break regions to depict how temporal variability of sound speed could change the dispersion characteristics of the broadband signal. Comparison between modeled and experimental data are provided. [Work supported by ONR OA program.]

High-resolution modal wavenumber estimation in range-dependent shallow water waveguides using vertical line arrays

Estimation of modal wavenumbers is important for inference of geoacoustic properties and matched field processing in shallow water waveguides. However, it is challenging in a range-dependent environment, because modal content varies locally in response to changes in the environment. Moreover, the scales of the spatial variations in the waveguide may be on the same order as the range aperture required for resolvability of the individual modes. To this end, high-resolution (HR) wavenumber estimation methods have been widely used. In this paper, the matrix pencil and MUSIC algorithms are generalized to geometry involving a synthetic horizontal aperture (SHA) formed by a towed acoustic source and a fixed full-spanning vertical line array (VLA). The performance of the proposed methods is evaluated by simulated data in a noisy shallow water environment. Numerical results show that, when compared with the previous methods, the proposed methods significantly outperform the previous methods in terms of aperture requirement.

Range-dependent geoacoustic inversion using equivalent environmental model in the presence of doppler effect.

Geoacoustic inversion using moving sensors attracts lots of interest due to the ease of deployment and low cost. However, the well-established techniques, such as matched-field inversion (MFI), may run into difficulties when the sensors are in a range-dependent environment for mismatch issues and increasing unknown parameters. Given a range-dependent environment, the paper focuses on the inversion using a synthetic aperture created by moving sensors in the presence of the Doppler effect. The derivation is given to obtain an equivalent range-independent environmental model for fast inversion, instead of a range-dependent one. The received fields are modified using the Doppler-shifted wavenumbers. The simulations and results of the SWellEx-96 experimental data verify the effectiveness of the proposed inversion method.

Rapid soundcape generate using energy flux modeling

The impact of anthropocentric sound on the living marine environment has been a growing area of concern. Human induced sound sources include shipping, siesmic exploration, pile driving, US Navy sonars, and miscellaneous (rare) explosions. The most ubiquitous and least regulated sound source is shipping, which dominates the ocean soundscape for frequencies below 500 Hz in much of the worlds oceans. Modeling of the ocean soundscape has been conducted using adiabatic modes, the parabolic equation and ray-tracing. In this paper, we present the modeling of the ocean soundscape (shipping and wind) with an energy flux algorithm. This analytic approach is very efficient and can handle mildly range-dependent environments. The flux model is used to generate regional sound models. With the inclusion of horizontal and vertical angle information at the model source position, this model can generate the noise directionality efficiently and can be then use for the performance of any particular array against directional noise in the ocean environment.

Deep-learning geoacoustic inversion using multi-range vertical array data in shallow water.

A multi-range vertical array data processing (MRP) method based on a convolutional neural network (CNN) is proposed to estimate geoacoustic parameters in shallow water. The network input is the normalized sample covariance matrices of the broadband multi-range data received by a vertical line array. Since the geoacoustic parameters (e.g., bottom sound speed, density, and attenuation) have different scales, the multi-task learning is used to estimate these parameters simultaneously. To reduce the influence of the uncertainty of the source position, the training and validation data are composed of the simulation data of different source depths. Simulation results demonstrate that compared with the conventional matched-field inversion (MFI), the CNN with MRP alleviates the coupling between the geoacoustic parameters and is more robust to different source depths in the shallow water environment. Based on the inversion results, better localization performance is achieved when the range-dependent environment is assumed to be a range-independent model. Real data from the East China Sea experiment are used to validate the MRP method. The results show that, compared with the MFI and the CNN with single-range vertical array data processing, the use of geoacoustic parameters from MRP achieves better localization performance.

Three-dimensional coupled-mode model and characteristics of low-frequency sound propagation in ocean waveguide with seamount topography

Large-scale topography, such as a seamount, substantially impacts low-frequency sound propagation in an ocean waveguide, limiting the application of low-frequency acoustic detecting techniques. A three-dimensional (3D) coupled-mode model is developed to calculate the acoustic field in an ocean waveguide with seamount topography and analyze the 3D effect. In this model, a correction is introduced in the bottom boundary, theoretically making the acoustic field satisfy the energy conservation. Furthermore, a large azimuth angle calculation range is obtained by using the operator theory and higher-order Padé approximation. Additionally, the model has advantages related to the coupling mode and parabolic equation theory. The couplings corresponding to the effects of range-dependent environment are fully considered, and the numerical implementation is kept feasible. After verifying the accuracy and reliability of the model, low-frequency sound propagation characteristics in the seamount environment are analyzed. The results indicate lateral variability in bathymetry can lead to out-of-plane effects such as the horizontal refraction phenomenon, while the coupling effect tends to restore the abnormal sound field and produces acoustic field diffraction behind the seamount. This model effectively considers the effects of the horizontal refraction and coupling, which are proportional to the scale of the seamount.

Adaptive array invariant in range-dependent environments with variable bathymetry.

The adaptive array invariant developed for source-range estimation in shallow water can incorporate the propagation-angle dependence of the waveguide invariant for an ideal waveguide (β=cos2θ) [Byun and Song, J. Acoust. Soc. Am. 148, 925-933 (2020)]. This paper extends the approach to weakly (adiabatic) range-dependent environments with variable bathymetry, wherein the waveguide invariant is a complex function of the bathymetry between source and receiver as well as the propagation angle in powers of sin2θ. For a given bathymetry, the adaptive array invariant can be implemented in an iterative fashion, and its remarkable performance is demonstrated using a short-aperture vertical array (2.8 m) for a broadband source (0.5-3.5 kHz) towed on a continental slope where the water depth varies from 87.5 to 55 m over a 5-km range.