Search Results (240)

Low-frequency ocean noise (50–500 Hz) was recorded by a single omnidirectional hydrophone in the open waters of the Chukchi Plateau from 31 August 2021 to 6 September 2021 (local time). After other non-wind interference was filtered out, wind-generated noise source levels (NSLs) were extracted from the wind-generated noise. The correlation coefficients between the one-third octave wind-generated NSLs and sea surface wind speed exceed 0.84, an improvement of approximately 10% compared to those between the raw data and the wind speed. For 200–500 Hz, the wind-generated NSLs are highly consistent with Wilson’s (1983) estimated curve. The 50–300 Hz results closely match those of Chapman and Cornish (1993) from vertical line array (VLA) measurements. Both demonstrate the feasibility of extracting wind-generated NSLs by utilizing a single omnidirectional hydrophone in the Chukchi Plateau’s open waters. Furthermore, the research results of wind speed dependence and frequency dependence can be applied to calculate wind-generated NSLs in the Chukchi Plateau. Wind-derived ocean ambient noise data are useful for background correction in underwater target detection, recognition, tracking, and positioning. Full article

MEMS acoustic sensors are a type of physical quantity sensor based on MEMS manufacturing technology for detecting sound waves. They utilize various sensitive structures such as thin films, cantilever beams, or cilia to collect acoustic energy, and use certain transduction principles to read out the generated strain, thereby obtaining the targeted acoustic signal’s information, such as its intensity, direction, and distribution. Due to their advantages in miniaturization, low power consumption, high precision, high consistency, high repeatability, high reliability, and ease of integration, MEMS acoustic sensors are widely applied in many areas, such as consumer electronics, industrial perception, military equipment, and health monitoring. Through different sensing mechanisms, they can be used to detect sound energy density, acoustic pressure distribution, and sound wave direction. This article focuses on piezoelectric, piezoresistive, capacitive, and optical MEMS acoustic sensors, showcasing their development in recent years, as well as innovations in their structure, process, and design methods. Then, this review compares the performance of devices with similar working principles. MEMS acoustic sensors have been increasingly widely applied in various fields, including traditional advantage areas such as microphones, stethoscopes, hydrophones, and ultrasound imaging, and cutting-edge fields such as biomedical wearable and implantable devices. Full article

To meet the critical need for compact, multifunctional acoustic vector sensors on deep-sea unmanned platforms such as acoustic profiling buoys and underwater gliders, we have developed a novel composite resonant acoustic vector sensor capable of large-depth operations. The sensor innovatively integrates the sound pressure channel and the vector channel, and utilizes the conjugate cross-spectrum between them to effectively reduce the isotropic noise, enhance the detection of weak signals from ships, and make up for the shortcomings of a single sound pressure channel and a vector channel. Certified to function reliably at depths up to 1500 m, field sea trials confirm its efficacy in deep-sea deployments, capturing essential marine environmental noise data. Key analysis during sea trials focused on marine ambient noise levels captured at frequencies of 65 Hz, 125 Hz, 315 Hz, 400 Hz, and 500 Hz, correlating these with changes in depth. The test results revealed the following insights: (a) At the same depth, the marine environmental noise level increases as the frequency decreases; (b) At the same frequency, the marine environmental noise level decreases with increasing depth; (c) Under favorable deep-sea conditions, the marine environmental noise level reaches 55 decibels (dB) at 500 Hz; (d) Noise levels tend to increase at various frequencies when surface ships are in proximity. These findings underscore its significant potential for enhancing deep-sea acoustic surveillance and exploration. Full article

This article explores the features of using hydroacoustic methods to measure and monitor climate-induced temperature variations along acoustic paths in the Sea of Japan. It delves into effective techniques for controlling and positioning of deep-sea autonomous measuring systems (DSAMS) for diverse applications. Theoretical and experimental findings from research conducted in the Sea of Japan in August 2023 along a 144.4 km acoustic route under summer–autumn hydrological conditions, including the aftermath of the powerful typhoon “Khanun”, are presented. The main hydrological regime characteristics for this period are compared with data obtained in 2022. This study explores the transmission of pulsed pseudorandom signals from a broad shelf into the deep area of the sea, with receptions occurring at depths of 69, 126, 680, and 914 m. An experiment was conducted to receive broadband pulse signals centered at a frequency of 400 Hz, located 144.4 km from the source of navigation signals (SNS), which is positioned on the shelf at a depth of 30 m in waters that are 45 m deep. A system of hydrophones, deployed to depths of up to 1000 m, was utilized to capture signal data, allowing for prolonged recording at fixed depths or during descent. An analysis of the experimentally acquired impulse characteristics revealed a series of ray arrivals lasting approximately 0.5 s, with a peak consistently observed across all depths. Findings from both full-scale and numerical experiments enabled the assessment of impulse characteristics within an acoustic waveguide, the calculation of effective signal propagation speeds at varying depths, and the development of conclusions regarding the viability of tackling control and positioning challenges for DSAMS at depths reaching up to 1000 m and distances spanning hundreds of kilometers from control stations. Full article

Towed streamer positioning is a vital and essential stage in marine seismic exploration, and accurate hydrophone coordinates exert a direct and significant influence on the quality and reliability of seismic imaging. Current methods predominantly rely on analytical polynomial models for towed streamer positioning; however, these models often produce significant errors when fitting to streamers with high curvature, particularly during turning scenarios. To address this limitation, this study introduces a novel multi-streamer analytical positioning method that uses a hybrid harmonic function to model the three-dimensional coordinates of streamers. This approach mitigates the substantial modeling errors associated with polynomial models in high-curvature conditions and better captures the dynamic characteristics of streamer fluctuations. Firstly, the mathematical model for the hybrid harmonic function is constructed. Then, the algorithmic implementation of the model is detailed, along with the derivation of the error equation and the multi-sensor fusion solution process. Finally, the validity of the model is verified using both simulated and field data. The results demonstrate that, in the turning scenario without added error, the proposed harmonic model improves simulation accuracy by 35.5% compared to the analytical polynomial model, and by 27.2% when error is introduced. For field data, accuracy improves by 18.1%, underscoring the model’s effectiveness in significantly reducing errors associated with polynomial models in turning scenarios. The performance of the harmonic function model is generally comparable to that of the polynomial model in straight scenarios. Full article

The present experimental study assessed the viability of utilizing an acoustic emission signal as a monitoring instrument to predict the chemical characteristics of wine throughout the alcoholic fermentation process. The purpose of this study is to acquire the acoustic emission signals generated by CO₂ bubbles to calculate the must density and monitor the kinetics of the alcoholic fermentation process. The kinetics of the process were evaluated in real time using a hydrophone immersed in the liquid within the fermentation tank. The measurements were conducted in multiple fermentation tanks at a winery engaged in the production of wines bearing the Rioja Denomination of Origin (D.O.) designation. Acoustic signals were acquired throughout the entirety of the fermentation process, via a sampling period of five minutes, and stored for subsequent processing. To validate the results, the measurements obtained manually in the laboratory by the winemaker were collected during this stage. Signal processing was conducted to extract descriptors from the acoustic signal and evaluate their correlation with the experimental data acquired during the process. The results of the analyses confirm that there is a high linear correlation between the density data obtained from the acoustic analysis and the density data obtained at the laboratory level, with determination coefficients exceeding 95%. The acoustic emission signal is a valuable decision-making tool for technicians and winemakers due to its sensitivity when describing variations in kinetics and density during the alcoholic fermentation process. Full article

Underwater direction-of-arrival (DOA) tracking using a hydrophone array is an important research subject in passive sonar signal processing. In this study, a DOA tracking algorithm based on a novel beam-domain signal processing technique is proposed to ensure robust DOA tracking of an interested underwater target under a low signal-to-noise ratio (SNR) environment. Firstly, the beam-based observation is designed and proposed, which innovatively applies beamforming after array-based observation to achieve specific spatial directivity. Next, the proportional–integral–differential (PID)-optimized Olen–Campton beamforming method (PIDBF) is designed and proposed in the beamforming process to achieve faster and more stable sidelobe control performance to enhance the SNR of the target. The adaptive dynamic beam window is designed and proposed to focusing the observation on more likely observation area. Then, by utilizing the extended Kalman filter (EKF) tracking framework, a novel PIDBF-optimized beam-domain DOA tracking algorithm (PIDBF-EKF) is proposed. Finally, simulations with different SNR scenarios and comprehensive analyses are made to verify the superior performance of the proposed DOA tracking approach. Full article

This study highlights the potential of aquariums as research platforms for bioacoustic research. Aquariums provide access to a wide variety of fish species, offering unique opportunities to characterize their acoustic features in controlled settings. In particular, we present a preliminary description of the acoustic characteristics of Myripristis jacobus, a soniferous species in the Holocentridae family, within a controlled environment at a zoological facility in the Canary Islands, Spain. Using two HydroMoth 1.0 hydrophones, we recorded vocalizations of the blackbar soldierfish in a glass tank, revealing a pulsed sound type with a peak frequency around 355 Hz (DS 64), offering a more precise characterization than previously available. The vocalizations exhibit two distinct patterns: short sequences with long pulse intervals and fast pulse trains with short inter-pulse intervals. Despite some limitations, this experimental setup highlights the efficacy of cost-effective methodologies in public aquariums for initial bioacoustic research. These findings contribute to the early stages of acoustic characterization of coastal fishes in the western central Atlantic, emphasizing the value of passive acoustic monitoring for ecological assessments and conservation efforts. Moreover, this study opens new avenues for considering the acoustic environment as a crucial factor in the welfare of captive fish, an aspect that has largely been overlooked in aquarium management. Full article

This paper is dedicated to the acoustic inversion of the vertical sound speed profiles (SSPs) in the underwater marine environment. The method of automatic differentiation is applied for the first time in this context. Representing the finite-difference Padé approximation of the propagation operator as a computational graph allows for the analytical computation of the gradient with respect to the SSP directly within the numerical scheme. The availability of the gradient, along with the high computational efficiency of the numerical method used, enables rapid inversion of the SSP based on acoustic measurements from a hydrophone array. It is demonstrated that local optimization methods can be effectively used for real-time sound speed inversion. Comparative analysis with existing methods shows the significant superiority of the proposed method in terms of computation speed. Full article

Gridless direction of arrival (DOA) estimation methods have garnered significant attention due to their ability to avoid grid mismatch errors, which can adversely affect the performance of high-resolution DOA estimation algorithms. However, most existing gridless methods are primarily restricted to applications involving uniform linear arrays or sparse linear arrays. In this paper, we derive the relationship between the element-domain covariance matrix and the angular-domain covariance matrix for arbitrary array geometries by expanding the steering vector using a Fourier series. Then, a deep neural network is designed to reconstruct the angular-domain covariance matrix from the sample covariance matrix and the gridless DOA estimation can be obtained by Root-MUSIC. Simulation results on arbitrary array geometries demonstrate that the proposed method outperforms existing methods like MUSIC, SPICE, and SBL in terms of resolution probability and DOA estimation accuracy, especially when the angular separation between targets is small. Additionally, the proposed method does not require any hyperparameter tuning, is robust to varying snapshot numbers, and has a lower computational complexity. Finally, real hydrophone data from the SWellEx-96 ocean experiment validates the effectiveness of the proposed method in practical underwater acoustic environments. Full article

Through extensive literature review, it has been found that sparse Bayesian learning (SBL) is mainly applied to traditional scalar hydrophones and is rarely applied to vector hydrophones. This article proposes a direction of arrival (DOA) estimation method for vector hydrophones based on SBL (Vector-SBL). Firstly, vector hydrophones capture both sound pressure and particle velocity, enabling the acquisition of multidimensional sound field information. Secondly, SBL accurately reconstructs the received vector signal, addressing challenges like low signal-to-noise ratio (SNR), limited snapshots, and coherent sources. Finally, precise DOA estimation is achieved for multiple sources without prior knowledge of their number. Simulation experiments have shown that compared with the OMP, MUSIC, and CBF algorithms, the proposed method exhibits higher DOA estimation accuracy under conditions of low SNR, small snapshots, multiple sources, and coherent sources. Furthermore, it demonstrates superior resolution when dealing with closely spaced signal sources. Full article

The vector hydrophone is playing a more and more prominent role in underwater acoustic engineering, and it is a research hotspot in many countries; however, it also has some shortcomings. For the mixed problem involving received signals in micro-electromechanical system (MEMS) vector hydrophones in the presence of a large amount of external environment noise, noise and drift inevitably occur. The distortion phenomenon makes further signal detection and recognition difficult. In this study, a new method for denoising MEMS vector hydrophones by combining ensemble empirical mode decomposition (EEMD) and singular spectrum analysis (SSA) is proposed to improve the utilization of received signals. First, the main frequency of the noise signal is transformed using a Fourier transform. Then, the noise signal is decomposed by EEMD to obtain the intrinsic mode function (IMF) component. The frequency of each IMF component in the center further determines that the IMF component belongs to the noise IMF component, invalid IMF component, or pure IMF component. Then, there are pure IMF reserved components, removing noisy IMF components and invalid IMF components. Finally, the desalinated IMF reconstructs the signal through SSA to obtain the denoised signal, which realizes the denoising processing of the signal, extracting the useful signal and removing the drift. The role of SSA is to effectively separate the trend noise and the periodic vibration noise. Compared to EEMD and SSA separately, the proposed EEMD-SSA algorithm has a better denoising effect and can achieve the removal of drift. Following that, EEMD-SSA is used to process the data measured by Fenhe. The experiment is carried out by the North University of China. The simulation and lake test results show that the proposed EEMD-SSA has certain practical research value. Full article

In order to study the feasibility of forming microtexture at the surface of 7050 aluminum alloy by laser-induced cavitation bubble, and how the density of microtexture influences its tribological properties, the evolution of the cavitation bubble was captured by a high-speed camera, and the underwater acoustic signal of evolution was collected by a fiber optic hydrophone system. This combined approach was used to study the effect of the cavitation bubble on 7050 aluminum alloy. The surface morphology of the microtexture was analyzed by a confocal microscope, and the tribological properties of the microtexture were analyzed by a friction testing machine. Then the feasibility of the preparation process was verified and the optimal density was obtained. The study shows that the microtexture on the surface of a sample is formed by the combined results of the plasma shock wave and the collapse shock wave. When the density of microtexture is less than or equal to 19.63%, the diameters of the micropits range from 478 μm to 578 μm, and the depths of the micropits range from 13.56 μm to 18.25 μm. This shows that the laser-induced cavitation bubble is able to form repeatable microtexture. The friction coefficient of the sample with microtexture is lower than that of the untextured sample, with an average friction coefficient of 0.16. This indicates that the microtexture formed by laser-induced cavitation bubble has a good lubrication effect. The sample with a density of 19.63% is uniform and smooth, having the minimum friction coefficient, with an average friction coefficient of 0.14. This paper provides a new approach for microtexture processing of metal materials. Full article

Matched field processing (MFP) is an established technique for source localization in known multipath acoustic environments. Unfortunately, in many situations, imperfect knowledge of the actual propagation environment and sidelobes due to modal interference prevent accurate propagation modeling and source localization via MFP. To suppress the sidelobes and improve the method’s robustness, a linear frequency-difference matched field processing (LFDMFP) method for estimating the source range is proposed. A two-neighbor-frequency high-order cross-spectrum between the measurement and the replica of each hydrophone of the vertical line array is first computed. The cost function can then be derived from the dual summation or double integral of the high-order cross-spectrum with respect to the depth of the hydrophones and the candidate sources of the replicas, where the range that corresponds to the minimum is the optimal estimation. Because of the larger modal interference distances, LFDMFP can efficiently provide only one optimal range within the same range search interval rather than some conventional matched field processing. The efficiency of the presented method was verified using simulations and experiments. The LFDMFP unambiguously estimated the source range in two experimental datasets with average relative errors of 2.2 and 1.9%. Full article

To solve the problem that the hydrophone arrays are disturbed by ocean noise when collecting signals in shallow seas, resulting in reduced accuracy and resolution of target orientation estimation, a direction-of-arrival (DOA) estimation algorithm based on iterative EMD interval thresholding (EMD-IIT) and off-grid sparse Bayesian learning is proposed. Firstly, the noisy signal acquired by the hydrophone array is denoised by the EMD-IIT algorithm. Secondly, the singular value decomposition is performed on the denoised signal, and then an off-grid sparse reconstruction model is established. Finally, the maximum a posteriori probability of the target signal is obtained by the Bayesian learning algorithm, and the DOA estimate of the target is derived to achieve the orientation estimation of the target. Simulation analysis and sea trial data results show that the algorithm achieves a resolution probability of 100% at an azimuthal separation of 8° between adjacent signal sources. At a low signal-to-noise ratio of −9 dB, the resolution probability reaches 100%. Compared with the conventional MUSIC-like and OGSBI-SVD algorithms, this algorithm can effectively eliminate noise interference and provides better performance in terms of localization accuracy, algorithm runtime, and algorithm robustness. Full article