Sound Speed Profile Research Articles

Improved calibration method for refraction errors in multibeam bathymetries with a wider range of water depths

Errors induced by inaccurate or insufficient sound speed profiles (SSPs) in the water column will cause refraction errors in multibeam bathymetries. Most existing methods focus on eliminating errors in shallow water. Thus, to address the problems in a wider range of water depths, a new method is developed. First, beams in each ping are divided into two parts with the nadir beam as a boundary, and beams in each part have one equivalent sound speed profile (ESSP). Then, the overlaps of adjacent swaths are used to estimate the gradients of ESSPs by minimizing the depth difference in the overlaps with the differential evolution (DE) algorithm. To verify the proposed method, two datasets, i.e., one with artificially introduced refraction errors from water depths within 24 m and the other with refraction errors from water depths within 300 m, are calibrated. The results show that the mean and standard deviation (SD) of the depth difference between the results of the proposed method and the in situ measurements in the shallow water data are approximately -0.006 m and 0.006 m, respectively. The mean and SD of the depth difference between the results of the proposed method and the in situ measurements in the deeper water data are approximately less than -0.066 m and 0.266 m, respectively.

Robust long-range source localization in the deep ocean using phase-only matched autoproduct processing.

Passive source localization in the deep ocean using array signal processing techniques is possible using an algorithm similar to matched field processing (MFP) that interrogates a measured frequency-difference autoproduct instead of a measured pressure field [Geroski and Dowling, J. Acoust. Soc. Am. 146, 4727-4739 (2019)]. These results are extended herein to a new MFP-style algorithm, phase-only matched autoproduct processing, that is more robust at source-array ranges as large as 225 km. This new algorithm is herein described and compared to three existing approaches. The performance of all four techniques is evaluated using measured ocean propagation data from the PhilSea10 experiment. These data nominally span a 12-month period; include six source-array ranges from 129 to 450 km; and involve signals with center frequencies between 172.5 and 275 Hz, and bandwidths of 60 to 100 Hz. In all cases, weight vectors are calculated assuming a range-independent environment using a single sound-speed profile measured near the receiving array. The frequency-differencing techniques considered here are capable of localizing all six sources, with varying levels of consistency, using single-digit-Hz difference frequencies. At source-array ranges up to and including 225 km, the new algorithm requires fewer signal samples for success and is more robust to the choice of difference frequencies.

Differential Geometry and Acoustics: A Survey

A connection between acoustic rays in a moving inhomogeneous fluid medium and the null geodesic of a pseudo-Riemannian manifold provides a mechanism to derive several well-known results commonly used in acoustic ray theory. Among these include ray integrals for depth dependent sound speed and current profiles commonly used in ocean and aero acoustic modelling. In this new paradigm these are derived by application of a symmetry of the effective metric tensor known as isometry. In addition to deriving well-known results, the application of the full machinery of differential geometry offers a unified approach to modelling acoustic fields in three dimensional random environments with time dependence by, (1) using conformal symmetry to simplify the geodesic equation, and (2) application of geodesic deviation as a generalization of geometric spread.

Bottom Attenuation Coefficient Inversion Based on the Modal Phase Difference Between Pressure and Vertical Velocity from a Single Vector Sensor

An inversion scheme based on time-warping is presented for estimating the attenuation coefficient of a sediment bottom using a single vector sensor, restricted to shallow water and using low-frequency impulsive sources. The attenuation information is extracted from the modal phase difference between pressure and vertical velocity. The method is derived from Pekeris waveguide theoretical equations and the eigen values are obtained using the normal mode model Kraken. Some changes are made to the time-warping process to mitigate the inherent interference between adjacent modes, which improves the phase extraction capabilities. Results are presented for a two-layer, homogeneous environment using the RAM propagation model for depth-dependent sound speed profile simulations. This version of RAM was updated to provide radial and vertical velocities. For additional generality, the technique is evaluated in the presence of white noise.

Improving the Estimation of Temperature and Salinity by Assimilation of Observed Sound Speed Profiles

AbstractSound Speed Profile (SSP) affecting underwater acoustics is closely related to the temperature and the salinity fields. It is of great value to obtain the temperature and the salinity information through the high-precision sound speed profiles. In this paper, a data assimilation scheme by introducing sound speed profiles as a new constraint is proposed within the framework of 3DVAR data assimilation (referenced as SSP-constraint 3DVAR (SSPC-3DVAR) ), which aims at improving the analysis accuracy of initial fields of the temperature and salinity in coastal sea areas. In order to validate the performance of the new assimilation scheme, ideal experiments are firstly carried out to show the advantages of the new proposed SSPC-3DVAR. Then the temperature, the salinity, and the SSP observations from field experiments in a coastal area are assimilated into the Princeton Ocean Model to validate the performance of short-time forecasts, adopting the SSPC-3DVAR scheme. Results show that it is efficient to improve the estimate accuracy by as much as 14.6% (11.1%) for the temperature (salinity), compared with the standard 3DVAR. It demonstrates that the proposed SSPC-3DVAR approach works better in practice than the standard 3DVAR and will primarily benefit from variously and widely distributed observations in the future.

Implosion in the Challenger Deep: Echo Sounding with the Shock Wave

Since HMS Challenger made the first sounding in the Mariana Trench in 1875, scientists and explorers have been seeking to establish the exact location and depth of the deepest part of the ocean. The scientific consensus is that the deepest depth is situated in the Challenger Deep, an abyss in the Mariana Trench with depths greater than 10,000 m. Since1952, when HMS Challenger II, following its namesake, returned to the Mariana Trench, 20 estimates (including the one from this study) of the depth of the Challenger Deep have been made. The location and depth estimates are as diverse as the methods used to obtain them; they range from early measurements with explosives and stop watches, to single- and multi-beam sonars, to submersibles, both crewed and remotely operated. In December 2014, we participated in an expedition to the Challenger Deep onboard Schmidt Ocean Institute’s R/V Falkor and deployed two free-falling, passive-acoustic instrument platforms, each with a glass-sphere pressure housing containing system electronics. At a nominal depth of 9,000 m, one of these housings imploded, creating a highly energetic shock wave that, as recorded by the other instrument, reflected multiple times from the sea surface and seafloor. From the arrival times of these multi-path pulses at the surviving instrument, in conjunction with a concurrent measurement of the sound speed profile in the water column, we obtained a highly constrained acoustic estimate of the Challenger Deep: 10,983 ± 6 m.

Sound speed gradients in mud

Various methods have been used to estimate sound speed profiles in mud at the New England Mud Patch. Some of these methods show large sound speed gradients of order 10 s-1. New measurements of the seabed reflection coefficient exhibit an angle of intromission over three octaves in frequency; these data constrain the range of possible sound speed gradient values. The data indicate that sound speed gradients must be quite weak, i.e., much smaller than |10 s-1|. This conclusion is supported by core data which indicate nearly constant porosity in most of the mud layer.

Collaborating Ray Tracing and AI Model for AUV-Assisted 3-D Underwater Sound-Speed Inversion

Three-dimensional sound-speed distribution is essential for large-scale underwater acoustic applications due to its influence on the signal propagation trajectory. However, it is labor, energy, and time consuming to measure sound speed by traditional methods because of the weak system maneuverability. In this article, an autonomous-underwater-vehicle-assisted underwater sound-speed inversion framework that collaborates ray tracing and artificial intelligence model is proposed to quickly obtain 3-D sound-speed distribution through multicoordinate inversions. An autoencoding-translation neural network is proposed to establish the nonlinear relationship from signal propagation time to the sound-speed profile (SSP), and the inversion time can be shortened with once forward propagation through the model. Robustness could be improved by inverting error-resistant implicit features into the SSP through the proposed translating neural network, whereas the implicit features are extracted from the autoencoder by denoising reconstruction of the input time information. To solve the overfitting problem and extend the training data set, virtual SSPs based on sparse feature points of real SSPs are generated. Simulation results show that our approach can provide a reliable and instantaneous monitoring of 3-D sound-speed distribution.

Rapid Modeling of the Sound Speed Field in the South China Sea Based on a Comprehensive Optimal LM-BP Artificial Neural Network

Ocean sound speed is an essential foundation for marine scientific research and marine engineering applications. In this article, a model based on a comprehensive optimal back propagation artificial neural network model is developed. The Levenberg–Marquardt algorithm is used to optimize the model, and the momentum term, normalization, and early termination method were used to predict the high precision marine sound speed profile. The sound speed profile was described by five indicators: date, time, latitude, longitude, and depth. The model used data from the CTD observation dataset of scientific investigation over the South China Sea (2009–2012) (108°–120° E, 6°–8° N), which includes comprehensive scientific investigation data from four voyages. The feasibility of modeling the sound speed field in the South China Sea is investigated. The proposed model uses the momentum term, normalization, and early termination in a traditional BP artificial neural network structure and mitigates issues with overtraining and difficulty when determining the BP neural network parameters. With the LM algorithm, a fast-modeling method for the sound field effectively achieves the precision requirement for sound speed prediction. Through the prediction and verification of the data from 2009 to 2012, the newly proposed optimized BP network model is shown to dramatically reduce the training time and improve precision compared to the traditional network model. Results showed that the root mean squared error decreased from 1.7903 m/s to 0.95732 m/s, and the training time decreased from 612.43 s to 4.231 s. Finally, the sound ray tracing simulations confirm that the model meets the accuracy requirements of acoustic sounding and verify the model’s feasibility for the real-time prediction of the vertical sound speed in saltwater bodies.

Variations of helioseismic parameters due to magnetic field generated by a flux transport model

The change of sound speed has been found at the base of the convection during the solar cycles, which can be used to constrain the solar internal magnetic field. We aim to check whether the magnetic field generated by the solar dynamo can lead to the cyclic variation of the sound speed detected through helioseismology. The basic configuration of magnetic field in the solar interior was obtained by using a Babcock-Leighton (BL) type flux transport dynamo. We reconstructed one-dimensional solar models by assimilating magnetic field generated by an established dynamo and examined their influences on the structural variables. The results show that magnetic field generated by the dynamo is able to cause noticeable change of the sound speed profile at the base of the convective zone during a solar cycle. Detailed features of this theoretical prediction are also similar to those of the helioseismic results in solar cycle 23 by adjusting the free parameters of the dynamo model.

Scattering of low-frequency acoustic waves from a moving source by the sea surface.

This paper examines the scattering of a monochromatic acoustic wave by sea-surface gravity waves in the 1-200 Hz frequency range. The source is moving in a straight line at a constant speed, and the acoustic waves are traveling upward in a refractive channel. Considering the scales of the problem, the small perturbation method coupled with the normal-mode theory and an asymptotic analysis are used to derive the first-order scattered pressure field p1. This method, established by Labianca and Harper [J. Acoust. Soc. Am. 61(2), 378-389 (1977)], allows p1 to be expressed with normal-mode functions, which are computed numerically using the in-house modal propagation code MOCTESUMA for any sound-speed profile. The pressure field is calculated in a deep-water configuration with a moving source inside a summer thermocline. First, the spatial distribution of p1 is found to follow the diffraction grating formula. Particular attention is drawn to the border between the propagative and evanescent regimes in which singularities in the theory lead to computational difficulties. Subsequently, the power spectral density of the pressure field is computed and the Doppler sidebands, asymmetrically shifted from the carrier frequency, are examined.

Underwater Target Ranging and Sound Speed Profile Inversion via Eigenray Propagation Time-Delay Matching

An underwater target ranging and sound speed profile (SSP) inversion algorithm for synchronous beacon is proposed. In the condition of actual SSP unavailable, based on the multipath propagation time-delay estimation, a genetic algorithm is employed to estimate the target range and SSP by eigenray propagation time-delay matching. Lake trial results show the algorithm could achieve target ranging and SSP inversion simultaneously.

Classification of Deep Sea Sound Speed Profiles in the Northwest Pacific Based on Cluster Analysis

Sound speed profile in ocean has significant seasonal and sea area distribution characteristics. Different sound speed profiles have different effects on underwater acoustic propagation, which makes the detection performance of sonar have significant differences. In order to study the distribution characteristics of sound speed profile in the Northwest Pacific, using WOA13 data set, calculate the number of types by application hierarchical clustering method, using cluster fuzzy c-means method classify sound speed profile, calculate the distribution area of various types in different seasons and typical sound speed profile structure. It is concluded that there are 6 types of sound speed profiles in Northwest pacific: Subarctic category, subarctic transitional category, subtropical transitional category, subtropical category, tropical transitional category and equatorial tropical category. The distribution area of these categories is generally zonal distribution. Except for the tropical transitional category and equatorial tropical category, the other categories have significant seasonal changes.

Sound field fluctuations in shallow water waveguide in the presence of nonlinear internal waves and estimation of their speed. ASIAEX experiment as a case study

Spectra of the sound field fluctuations in shallow water waveguide in the presence of nonlinear internal waves (NIW) are studied and used for solution of inverse problem: to estimate variability of speed of NIW using results of ASIAEX experiment. ASIAEX was carried out in the South China sea since April 29 until May 14, 2001, a few tens of solitary NIW with amplitude up to 100 m were registered, moving toward the beach. Sound pulses (M-sequences, frequency 224 Hz) from the source were propagating in narrowing channel (350 m–120 m, distance 30 km) toward the beach in the presence of NIW. It was shown earlier by authors that spectrum of fluctuations measured during NIW’s motion contains peaks at frequencies F depending on speed v of NIW and scales of interference beating D of waveguide modes F ∼ v/D. D depends on bathymetry and sound speed profile in a waveguide. Using measurement of peak frequencies and known values of D, and using matching procedure between modeling and experimental data, variations of v were found for set of above mentioned events of NIW passing. Results were compared with direct measurements using satellite observations. [Work was supported by RFBR under Grant No. 20-55-S52005.]

Teaching underwater acoustics and sonar during the COVID pandemic

USNA’s Underwater Acoustics and Sonar (SP411) course, taught in a studio classroom, can seat 36 students with 5 experimental/computer workstations on each side of the classroom. This non-laboratory course relies on hands-on demos and in-class mini-laboratory experiences bringing theoretical concepts and experimental aspects of sound propagation and detection theory to life. Experiments include: (a) sound speed versus temperature in water, (b) beam pattern functions versus angle for multi-element arrays, (c) Fourier analysis of periodic waveforms including rectangular pulses, and (d) square law detection of signals plus noise—generating receiving operating characteristic ROC curves. Computer visualizations using Mathematica included phasor addition of signals, N-element array superposition for directivity analysis and a user friendly ray tracing program implementing any sound speed versus depth profile. On 20 March, 2020, the USNA entered the pandemic era by requiring remote learning for all 4100 midshipman, commencing shortly after spring break. Remote learning in SP411 was asynchronous, devoid of lectures, including handouts and videos of wave effects and worked examples. Mathematica visualizations replaced experiments and extra instruction (in different time zones) was always available. Co-author LEB’s photoacoustic imaging experiments, done remotely, used homemade electronics (pulsed LED driver and low-noise amplifiers)—keeping future midshipmen research going.

Undersea detection of aerial targets

The undersea detection of aerial targets is a difficult acoustic problem that was first examined almost 50 years ago and has received renewed interest lately for several important applications. In this work, the authors are interested in the trade space of feasibility for airborne sources at different altitudes and atmospheric conditions and for undersea receivers subject to different sound speed and bathymetry profiles.

Geoacoustic inversion of modal dispersion on the New England Mud Patch. I: Experimental quantification of information content in higher-order modes

This paper presents the results from a geoacoustic inversion study performed using a combustive sound source signal recorded on a vertical line array during the 2017 Seabed Characterization Experiment (SBCEX17). A single receiver modal estimation method (source deconvolution and warping) is recursively applied along the array channels to estimate modal time-frequency dispersion, resulting in modal dispersion data for 18 modes between modes 1 and 21. These data are then used as an input for trans-dimensional Bayesian geoacoustic inversion. The paper compares inversion results obtained with subsets of modes (1 to 7 and 1 to 15) to those obtained with the whole set (modes 1 to 21) to explore the data information content associated with high-order modes. The study shows that high-order modes enable the resolution of fine details in the seabed sound-speed profile, such as a small sound speed increase over the first 8 m of the seabed (i.e., within the upper portion of the so-called “mud layer,” an important feature of the experiment area). [Work supported by the Office of Naval Research.]

Marine Acoustic Zones of Australia

Underwater sound is modelled and mapped for purposes ranging from localised environmental impact assessments of individual offshore developments to large-scale marine spatial planning. As the area to be modelled increases, so does the computational effort. The effort is more easily handled if broken down into smaller regions that could be modelled separately and their results merged. The goal of our study was to split the Australian maritime Exclusive Economic Zone (EEZ) into a set of smaller acoustic zones, whereby each zone is characterised by a set of environmental parameters that vary more across than within zones. The environmental parameters chosen reflect the hydroacoustic (e.g., water column sound speed profile), geoacoustic (e.g., sound speeds and absorption coefficients for compressional and shear waves), and bathymetric (i.e., seafloor depth and slope) parameters that directly affect the way in which sound propagates. We present a multivariate Gaussian mixture model, modified to handle input vectors (sound speed profiles) of variable length, and fitted by an expectation-maximization algorithm, that clustered the environmental parameters into 20 maritime acoustic zones corresponding to 28 geographically separated locations. Mean zone parameters and shape files are available for download. The zones may be used to map, for example, underwater sound from commercial shipping within the entire Australian EEZ.

Underwater stealth metasurfaces composed of split-orifice–conduit hybrid resonators

The development of sound-absorbing materials for noise reduction in daily life has been a prolonged issue that also applies to a recognized need for submarine anechoic tiles to stay independent from SONAR (SOund NAvigation Ranging). Here, we present an underwater stealth metasurface that uses split-orifice–conduit (SOC) hybrid resonators to significantly reduce its acoustic reflectance. A theoretical analysis of SOC elements provides an approach to quantifying acoustic characteristics using the transfer matrix method in a single metasurface. The findings confirm that we can tune the absorption with respect to a resonating frequency by adjusting geometrical parameters. Utilizing a hybrid mechanism that enables easy access to coupled resonances, we obtain broadband absorption spectra even in the presence of a covariant sound speed profile in the deep sea and a thermoviscous effect on unit cells of the metasurface. Such a metasurface will provide a further step toward developing feasible underwater stealth technologies for submarines and remains to be experimentally demonstrated.

Predicting Acoustic Variability: Pragmatic Considerations for Selecting a Stochastic or Deterministic Approach

Sonar performance prediction models require environmental inputs, including bottom depth and composition, sound-speed profile (SSP), and wave or wind conditions. Temporal and spatial variation and measurement uncertainties in environmental inputs result in uncertain model outputs. Ideally, acoustic fluctuations could be predicted from input parameter variability using a suitable modeling framework. A data set consisting of 460 SSPs and acoustic transmission loss (TL) measurements between 300 and 900 Hz was acquired during GLISTEN15, a 2015 Mediterranean Sea trial led by North Atlantic Treaty Organization's Centre for Maritime Research and Experimentation. The TL was measured in 5-min sampling periods at fixed source-to-receiver ranges of 0.5-10 km over two separate days. A gradual change in TL as large as 15 dB over 5 min was observed at some receivers and frequencies. Predicted TL variability was compared to measured TL variability by using the SSPs as inputs to an acoustic propagation model. Purely stochastic modeling either over- or underpredicted variability, depending on the temporal and spatial separation of the SSPs used as inputs. In this article, an internal wave model derived from the SSP time series was used to demonstrate the possible effect of internal waves propagating perpendicular to the source-receiver direction. The best agreement between modeled and measured variability was obtained for internal waves of 1536-s period and 0.8-1.6-m amplitude. In this way, an approach that included a physically plausible model of internal wave dynamics grounded in a few relevant in situ measurements provided good predictions of observed TL variability and a reasonable explanation of its origin.