Sound Velocity Profile Research Articles

Simulation of horizontal refraction of continental slope in the southern continental slope of the South China Sea

Abstract Sound waves are significantly influenced by boundaries during their propagation in certain environmental conditions. The extent of this impact is related to the complexity of the boundary, such as in the case of slopes and seamounts. In these areas, sound waves may deviate from their original paths, resulting in three-dimensional effects. Recent experiments and simulations have demonstrated that three-dimensional effects occur when sound waves propagate over seamounts in the South China Sea, leading to larger acoustic shadow regions. However, there are limited studies on 3D acoustic propagation based on measured slope topography or database topography. In this study, the topography of the South China Sea area database is selected, and the measured sound velocity profile and seabed acoustic parameters in the South China Sea are taken into considered. The FOR3D sound field calculation model is used to calculate the N×2D and 3D results. The simulation results show that in the southern continental slope region of the South China Sea, when the sound source frequency is 50 Hz, the acoustic wave exhibits significant horizontal refraction with a refraction angle of approximately 13°.

Oceanographic Characteristics in the Three International Indonesian Archipelago Sea Lanes (IASLs) Region: Implications for Underwater Acoustics System

Graphical Abstract Highlight Research The IASL-1 entry portal in the southern and northern regions shows the emergent SOFAR channels. The shadow zone and the existence of a SOFAR deep sound channel in the IASL-2 and IASL-3 routes can be triggered by the emergent “saddle” SVP pattern. The variability seasonally and interannually due to variations in seawater properties stratification plays an important role in SOFAR channel appearances in IASLs. The diverse oceanographic characteristics of IASLs necessitate the implementation of sustainable marine geospatial data. Abstract The Indonesian Maritime Continent (IMC) provides three international sea lanes, known as the Indonesian Archipelago Sea Lanes (IASLs), allowing ships to navigate across territorial waters between the Pacific and Indian Oceans and vice versa. Gaining knowledge about the distinct oceanographic characteristics of the three IASLs can offer valuable insight into maritime safety and sustainable marine resource management. This study aims to review oceanographic characteristics in IASL regions from available past studies to provide a comprehensive insight into the processes and dynamical oceanography in the IASL region and its implications for underwater acoustic patterns. The results of research found that the IASL-1 route is characterized by a shallow shelf passage with homogeneous sound velocity profile (SVP) but a deep and narrow entry portal in the southern and northern SOFAR channels. Seasonal reversal monsoonal wind-driven current dominates the circulation. The IASL-2 and IASL-3 routes convey a deep and narrow passage with complexity of sea-air interactions; they vary on seasonal and interannual time scales. These IASLs emerge with the “saddle” SVP, which can trigger the shadow zone and the existence of a SOFAR deep sound channel that varies seasonally and interannually due to variations in seawater properties stratification. The diverse oceanographic characteristics discussed above significantly influence the underwater object detection equipment, the planning time, and the strategies for underwater defense systems. Due to these implications, it is necessary to utilize marine geospatial database. Subsequently, these data may be utilized to facilitate policy-making and provide approximations for marine activities and management along the IASLs.

An adaptive stratification algorithm based on gradient fitting deviation and its application to acoustic ray-tracing algorithm

Accurate underwater positioning is a challenging task for complex marine environments where the study of sound velocity profiles (SVPs) is essential. To overcome the problem that the original SVP reduces the computational efficiency of the ray-tracing algorithm due to great capacity of data, this paper simplifies the SVP. The nature of the SVP and its influence on accurate underwater positioning are discussed. An adaptive stratification algorithm applicable to the ray-tracing algorithm is proposed, based on the gradient fitting deviation and characterized by the fitting treatment of the sound velocity gradient by the Fourier method. Measured SVP data and acoustic positioning data were used to validate this algorithm in the context of acoustic ray-tracing algorithm, to analyze and compare the simplification rates before and after SVP simplification, and the effect on the positioning accuracy. The experimental results in the shallow sea (water depth of 60 m) show that the simplification rate of the SVP is more than 95.56%, and the RMS of the deviation of the ray-tracing algorithm is better than 0.0112 m when determining the optimal number of unfolding levels and threshold; the experimental results in the deep sea (water depth of 1900 m) show that the simplification rate of the SVP is more than 99%, and the RMS of the deviation of the ray-tracing algorithm is better than 0.5 m. This indicates that, the algorithm can reconstruct the original SVP well and implement the automatic hierarchical simplification of the SVP while ensuring the positioning accuracy.

Interacting quark star with pressure anisotropy and recent astrophysical observations

This paper investigates the internal structure and equation of state (EoS) of quark stars (QS) with pressure anisotropy, incorporating recent astrophysical observations. Utilizing perturbative QCD corrections and color superconductivity, the EoS is expressed as a dimensionless function dependent on a single parameter, providing a comprehensive exploration of strong interaction effects. By rescaling the EoS and introducing dimensionless variables, the study encompasses scenarios ranging from noninteracting quark matter to extreme stiffness characterized by a parameter, λ̄. Anisotropic QS configurations are constructed using a spherically symmetric metric, with locally anisotropic matter described by a generalized EoS for tangential pressure. The Tolman–Oppenheimer–Volkoff equations governing star structure are presented in dimensionless form, and numerical solutions explore the parameter space defined by effective bag constants and λ̄. Mass–radius relations and the compactness of anisotropic QSs are analyzed under various model parameter variations, considering constraints from pulsar masses and gravitational wave phenomena. The study highlights the influence of pressure anisotropy on the maximum mass of QSs and discusses the impact of model parameters on internal properties. Additionally, the paper considers static stability, adiabatic index, and sound velocity profiles, providing a comprehensive understanding of QS behavior. Overall, this investigation contributes valuable insights into the properties of QSs and their compatibility with observational constraints, offering a detailed exploration of their EoS and internal structure.

The role of pressure anisotropy on quark stars in gravity’s rainbow

This work is seeking for the existence of stable quark stars (QSs) in the framework of a modified theory of gravity known as gravity’s rainbow. This modification comes from the fact that the geometry of spacetime depends on the energy of the test particle. We solve numerically the modified TOV equations and present the mass–radius (M–R) diagram for quark matter equations of state. To constrain the allowed values of the model parameters, we use current astrophysical measurements of the masses and radii of neutron stars. Finally, we investigate the dynamical stability of the hydrostatic equilibrium equations in gravity’s rainbow by analyzing the static stability, adiabatic index, and sound velocity profiles.

Ultra-fast calculation method of incident angle based on underwater acoustic round-trip positioning

In underwater acoustic round-trip positioning, the incident angle calculation in constant gradient acoustic ray tracing significantly hinders the efficiency of positioning calculation. To address this issue, we proposed an ultra-fast calculation method for determining incident angle based on underwater acoustic round-trip positioning. Specifically, the method employs the k-mean++ clustering algorithm to streamline the sound velocity profile. Additionally, a function formula for the incident angle is constructed, and its partial derivative with respect to Snell's constant is derived. Finally, Newton's method is applied to iteratively calculate the incident angles of the signal emission and reception, respectively. The simulation test results demonstrate that the proposed method reduces the positioning calculation time by 80.123%, 80.105%, 80.136%, and 80.104% on four transponders compared to the traditional method. In the field experiment, the proposed method is superior to the traditional method by 81.693% in positioning calculation time. These findings indicate the significant superiority of the proposed method in positioning calculation efficiency compared to the traditional method.

An improved algorithm based on equivalent sound velocity profile method at large incident angle

An improved algorithm based on equivalent sound velocity profile method at large incident angle

Passive acoustic localization using dictionary learning

Ray-trace simulations are used to demonstrate the use of Dictionary Learning to improve passive localization of a source monitored with a vertical linear acoustic array. The learned dictionary, generated using historical sound velocity profile (SVP) data from a region of interest, is an over complete, sparse representation of the SVP training set. By minimizing an objective function that measures the differences between multipath reception intervals detected at a receiver for propagation through candidate and baseline SVP profiles, we show that an optimal SVP match to the “unknown” baseline can be reconstructed by an efficient dictionary search. Ray traces back-propagated through the reconstructed SVP according to beamformed receive angles computed with the baseline SVP are then found to well estimate the source position as the centroid of a cluster of multipath signal intersections. The accuracy for small unit-sparsity dictionaries of size up to 50 was evaluated on a randomly sampled, 30 SVP testing set obtained from an area close to that of the training set, demonstrating mean location errors less than 5% in both distance and depth. Five representative profiles spanning the range of observed sound speed variations were used to assess localization performance at source depths from 50 to 450 m and at source ranges from 2000 to 4500 m. Compared to using the average sound speed profile to estimate source position, using the learned dictionary produced a general performance increase in position accuracy.

Acoustic propagation modeling using sound velocity profiles estimated from high resolution temperature data

An accurate sound velocity profile (SVP) is an important input for underwater acoustic propagation modeling. The SVP is largely driven by the temperature of the water column, especially at shallower depths. Measuring the SVP in high spatial and temporal resolution is challenging with traditional instrumentation, however techniques exist to produce high resolution temperature measurements that can be used to derive estimates of the SVP. Fiber optic distributed temperature sensing (DTS) offers an improvement of several orders of magnitude over traditional singular point measurement devices and has the ability to measure temperature over large range and depth scales in an efficient manner. A DTS system was towed for 172 nm off the coast of New England over several days. The measured temperature data was used to estimate the SVP across the range and depth and will be compared to traditional environmental data sets, such as HYCOM. A comparison of modeled acoustic propagation using different resolution SVPs will be presented.

Adaptive Sound Velocity Profile Prediction Method Based on Deep Reinforcement Learning

Adaptive Sound Velocity Profile Prediction Method Based on Deep Reinforcement Learning

A rigorous real-time acoustic positioning method for ocean bottom seismic exploration

The conventional technique for positioning seafloor geophones in ocean bottom seismic exploration encounters several challenges, including the significant impact of outliers on positioning results, underutilization of high-precision observations, and low efficiency in real-time data processing. These issues inevitably affect the quality of seismic exploration outcomes. To address these challenges and enhance the accuracy of geophone positioning, this paper proposes a rigorous real-time acoustic positioning method for geophones based on sequential adjustment and Baarda's outlier detection approach. The proposed method comprises three key steps: grouping the original acoustic observations, constructing the intra-group acoustic positioning model, and synthesizing the positioning results across the different groups. The validity and practicality of this approach are confirmed through a simulation experiment as well as the field experiment conducted in the Bohai Sea, China. The results demonstrate that the proposed method effectively eliminates outliers in the original observations and maximizes the utilization of high-quality observations. Compared to traditional acoustic positioning methods, it significantly reduces positioning errors from meters to decimeters, and in some cases can achieve centimeter-level precision. When the sound velocity profile in the operating sea area is measured, the method can attain the posterior standard deviation at the millimeter level and positioning errors within 10 cm. When the sound velocity profile is unknown, the method can achieve the posterior standard deviation at centimeter-level and positioning errors of approximately 20 cm.

Analysis of Nuclear Explosion Detection Capability of IMS Hydroacoustic Network

The Comprehensive Nuclear Test Ban Treaty (CTBT) organization has established a hydroacoustic network to ensure the effective detection of nuclear explosions in the vast ocean and in the atmosphere over it in order to effectively guarantee the implementation of the treaty. To assess its effectiveness, according to the reciprocity of underwater acoustic field, this study employs the hydrophone position as the central sound source and utilizes the parabolic equation, along with seabed topography and sound velocity profile data, to estimate the transmission loss. Background noise levels of station evaluation are conducted by using historical data so as to estimate the underwater nuclear explosion sound source level via a passive sonar equation. Utilizing the full ship shock trial (FSST) results of the “Ford” aircraft carrier on June 18, 2021, as a case study, the detection capability of the HA10 station for nuclear explosions is investigated. Subsequently, the network’s overall detection capability was evaluated using the source level at 20 Hz corresponding to a 1 kiloton nuclear explosion yield as a reference. Findings indicate the network’s proficiency in identifying long‐distance propagation signals, particularly those with high explosion source levels within the sound fixing and ranging (SOFAR) channel. The sensitivity analysis demonstrates the network’s ability to detect explosions smaller than 1 kg equivalent in close proximity to a station, and larger explosions exceeding 1 kg or 1 ton at greater distances. This evaluation underscores the network’s significance in detecting and monitoring underwater nuclear explosions across extensive oceanic regions.

A Sound Velocity Profile Stratification Method Based on Maximum Density and Maximum Distance Clustering

In the field of deep-sea positioning, this paper aims to enhance accuracy and computational efficiency in positioning calculations. We propose an improved method based on layered clustering of sound velocity profiles, where the profiles are stratified according to maximum distance and maximum density. Subsequently, a secondary curve fitting is applied to the stratified data. Ultimately, the underwater positioning is conducted using the sound velocity profiles’ post-layered fitting. We compare our approach with traditional methods such as k-means clustering, layered clustering, and gradient-based stratification. Experimental results demonstrate that, in the application scenario of a USBL system with a transducer tilted at 30°, and under the premise of autonomously controlling the number of layers, our method significantly improves positioning accuracy.

Two-Step Correction Based on In-Situ Sound Speed Measurements for USBL Precise Real-Time Positioning

The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical factor limiting the positioning performance. The conventional strategy adopts a fixed sound velocity profile (SVP) to correct the spatial variation, especially in the vertical direction. However, SVP is actually time-varying, and ignoring this kind of variation will lead to a worse estimation of ARVs’coordinates. In this contribution, we propose a two-step sound speed correction method, where, firstly, the deviation due to the acoustic ray bending effect is corrected by the depth-based ray-tracing policy with the fixed SVP. Then, the temporal variation of SVP is considered, and the fixed SVP is adaptively adjusted according to the in situ sound velocity (SV) measurements provided by the conductivity–temperature–depth (CTD) sensor equipped at the ARV. The proposed method is verified by semi-physical simulation and sea-trail dataset in the South China Sea. When compared to the fixed-SVP method, average positioning accuracy with the resilient SVP be improved by 8%, 21%, and 26% in the east, north, and up directions, respectively. The results demonstrate that the proposed method can efficiently improve the adaptability of sound speed observations and deliver better performance in USBL real-time positioning.

Sound Velocity Profiles Time Series Prediction Method Based on EMD-NARX Model

To solve the problem of SVP (Sound velocity profiles) representative error caused by the difficulty of obtaining continuous time series SVP in deep-sea operations, an SVP timing prediction method combining EMD (Empirical mode decomposition) and NARX (Nonlinear autoregressive neural network with external input) is proposed. To begin with, the time-series SVP are stratified according to different depths, and the time-series variation curves of sound velocity at different depths are obtained; Furthermore, the EMD is used to decompose the time series variation curve of sound velocity into multiple IMF (Intrinsic mode function) components, each component contains local characteristic signals of different time scales of the original signal. The NARX is used to establish a prediction model for each IMF components, and the prediction values of the sound velocity at different depths are obtained. The EMD-NARX, NARX and polynomial fitting model are analyzed and verified by Argo buoys data in the South China Sea, and the results of the experiment show that EMD-NARX improves the time series prediction accuracy of sound velocity by 32.24% and 65.15% compared with NARX and polynomial fitting, respectively, so EMD-NARX has a good prediction effect on the time series SVP of the deep sea.

Ocean ambient noise field modelling and the optimized noise term

The objective of this thesis is to determine the frequency and wind-wave forcing dependent effective sea surface noise source level per unit area extracted from the hourly minimum sound power levels of six month-long acoustic recordings. The effect of the propagation environment is accounted for using Bellhop. The simulated environment is configured using climatological sound velocity profiles to capture seasonal effects and bottom sound speed estimates made from seabed sediment maps. Hourly meteorological data were extracted from ERA5 providing relevant wind and wave parameters from which noise levels may be predicted. A weighted composite model consisting of neutral wind and significant wave height leveraging the two-term exponential regression function proved to maximize model R2. Received level data originating from 16 hydrophone stations in the North Atlantic and Labrador Sea were combined with the Bellhop TL simulations in order to produce estimates of the effective noise source level per unit area (NSL/A) for changing surface environmental conditions and inter-compared. Hourly minimum sound power level derived model-data comparisons using horizontal wind speed magnitude 10 m above sea level expressed a decrease in NSL/A estimates versus Kewley (1990) by 10 to 15 dB from 1 to 3 kHz.

Influences of Ocean Environment on Sound Propagation Based on Bellhop Model

The actual marine environment is complex and changeable, and different marine environmental factors have an important impact on sound propagation. Based on the Bellhop model, this paper studies the sound propagation characteristics under different marine environmental factors, quantitatively analyzes the differences in the sound propagation characteristics when the seabed topography, sound velocity profile, and sound source emission angle change, and summarizes the impact on underwater sound propagation under different conditions, so as to provide a theoretical numerical basis for the ocean sound field in the actual complex environment, and further serve the research of the ocean sound field.

Analysis of Sound Fluctuations in Shallow Water in High Sea States

Sound intensity fluctuation plays a significant role in underwater acoustic studies. In this article, an experiment was conducted in the South China Sea using a buoy system that autonomously emitted and received sound signals to obtain data on sound fluctuations under different wind conditions (in windy weather) for about 179 h. Results showed that the fluctuation of the transmission loss in a fixed position reached up to 15–20 dB. Different potential reasons for this transmission loss fluctuation are analyzed. Using the wind speed data provided by the Earth system, the sea surface wave spectrum model, and the bubble layer model, the fluctuation of the transmission loss was simulated based on the modified Ramsurf sound propagation model. The simulation and experimental results were in good agreement with each other. Therefore, the fluctuation of the transmission loss due to wind-generated waves in high sea states should be considered while studying underwater communication, particularly in shallow water with a positive gradient sound velocity profile.

Node Depth Adjustment Based Target Tracking in Sparse Underwater Sensor Networks

Due to the limited energy in underwater sensor networks, underwater nodes need to be deployed sparsely. However, sparse USNs will lead to poor tracking coverage and detection capability. To solve these problems, the mobility of nodes in depth can be utilized to optimize the node topology to achieve data fusion more reliably and effectively. In this paper, for underwater target tracking, a node depth adjustment algorithm is proposed. Firstly, after introducing the sound velocity profile on acoustic signal transmission, the asynchronous particle filter algorithm based on delay estimation is improved, which makes the filter more suitable for an underwater environment. Secondly, the influence of node topology on the tracking accuracy is analyzed, and the optimization problem of node depth adjustment is constructed, in which the depth-related Fisher Information Matrix is designed as the optimization criterion. Thirdly, for scenarios in which the target depth is either known or unknown, the analytical method and the interior point method are employed to solve the problem, respectively, and the optimal depth adjustment strategies in corresponding scenarios are obtained. The simulation results show that the proposed algorithm can fully adjust the node depth and achieve a more accurate tracking performance.

Self-diffusion coefficient and sound velocity of Fe-Ni-O fluid: Implications for the stratification of Earth's outer core

It is experimentally reported that the stratified layer atop Earth's outer core is hundreds of kilometers thick with a maximum sound velocity reduction of 0.3% relative to the preliminary reference Earth model. However, why the sound velocity atop the outer core is reduced remains theoretically unclear. In this paper, the Ni and vital light O in the outer core were both considered to have implications for the stratification of Earth's core, including the stratification thickness and the sound velocity profile. Ab initio molecular dynamics simulations were performed on the Fe-Ni-O fluid under the conditions of Earth's outer core, and the self-diffusion coefficients and ion-ion dynamic structure factors were calculated. The self-diffusion coefficient of O was calculated to be (19.56 ± 0.83) × 10−9 m2s−1 at the core-mantle boundary. Combining the diffusion equation with the time evolution of the O self-diffusion coefficient, the calculated stratification thickness at present is 194.7 km. The calculated ion-ion dynamic structural factors indicate that the sound velocity in the outmost outer core near the stratified layer is 7.86 km/s, which is lower than the preliminary reference Earth model values (∼8.05 km/s). These results show that Fe-Ni-O liquid atop the outer core featuring an appropriate thickness and a reduced sound velocity, thereby shedding light on the dynamic behavior of Earth's core.