Search

This paper describes the Santos Basin Underwater Soundscape Monitoring Project (PMPAS-BS), a Brazilian ocean soundscape monitoring initiative. The main objective of the project is to quantify and assess hydroacoustic noise of anthropogenic origin in a large sedimentary basin extending from 23° S to 28° S on the southeastern Brazilian continental margin of the South Atlantic Ocean. Noise associated with oil and gas (O&G) exploration and production activities is the primary target, but this oceanic region also has busy shipping lanes for commercial, military, and fishing vessels. The two main hubs of Brazil’s export and import of goods by sea are located in this region: Santos and Rio de Janeiro ports. The project has three measurement components: mobile monitoring based on gliders and drifting acoustic profilers, fixed shallow-water monitoring based on acoustic measurements at coastal stations near shipping lanes associated with exploration and production activities in the Santos Basin, and fixed oceanic monitoring based on deep-water mooring lines equipped with passive autonomous acoustic recorders near production units, shipping lanes, and areas with lower intensity of O&G activities (pristine or reference sites). Numerical modeling of anthropogenic underwater acoustic noise has also been included as a fourth project component. The PMPAS-BS covers an area of more than 251,000 km² and uses several instruments with different methods and sensors for acoustic measurements. Its results provide current sound levels over a very large region of the western South Atlantic, both in areas more and less affected by anthropogenic activities. [ABSTRACT FROM AUTHOR]

Sound exposure studies require replicated sound treatments for the results to be representative for sound classes in general. Additionally, reused treatments in replicated designs need to be accounted for statistically. The lack hereof is referred to as simple and sacrificial pseudoreplication, respectively, and results should be interpreted accordingly. We quantified the occurrence of these issues and subsequent interpretation of results in 104 underwater sound exposure studies (2019–2023). The majority of the studies (85%) did not replicate sound treatments. From the ones that did, most did not statistically acknowledge the hierarchical structure of the data. Unreplicated treatment designs limit the generalizability of the findings. Nevertheless, only small differences were found in how the results of unreplicated and replicated treatment designs were interpreted. This commentary aims to provide guidance in the design, analysis and interpretation of sound exposure studies, which are equally valid for aquatic and terrestrial research. • We quantified sound treatment pseudoreplication in underwater sound exposure studies. • Most papers did not replicate sound treatments (simple pseudoreplication). • Hierarchical treatment designs were often not statistically acknowledged. • We hope to contribute to reducing pseudoreplication in sound exposure studies. [ABSTRACT FROM AUTHOR]

The superhydrophobicity of submerged surfaces typically pertains to the trapped air film at the liquid–solid interface, subject to wettability transitions from a Cassie–Baxter state to more unstable states that gradually collapse to high retention regimes, which are energetically more favorable. In this work, the dynamic evolution of those transient metastable states is correlated to the underwater acoustic performance of laser textured superhydrophobic surfaces, resolving the dependence of the ultrasound spectral response with the immersion time to capture the genuine contribution of the hierarchical subwavelength morphology, regardless of the air layer effects. Acoustic wave attenuation of the incident ultrasound energy is extensively quantified in transmission, accounting for instantaneous broadband sound blocking (>30 dB) within the spectral range 0.5–1.5 MHz. As a result of the air layer detachment with the immersion time, transmission coefficients increase accordingly, while acoustic fields in reflection unexpectedly evolve toward stealthiness and naïve acoustic camouflage, mostly ascribable to dissipative mechanisms at air layer interfaces. The intrinsic decay of the air layer effect is tentatively determined at different frequencies, since quantitative understanding of the transient lifetime governing underwater surface wettability is critical to design stable superhydrophobic character of laser induced subwavelength metastructures on the most promising acoustic materials – from eco‐friendly natural to artificial. [ABSTRACT FROM AUTHOR]

Due to the influence of the complex underwater environment, the sound speed constantly changes, resulting in the acoustic signal propagation trajectory being curved, which greatly affects the positioning accuracy of the underwater long baseline (LBL) system. In this paper, an improved LBL positioning method based on a B-spline surface for fitting the effective sound speed table (ESST) is proposed. Firstly, according to the underwater sound speed profile, the discrete ESST of each measurement station is constructed before the positioning test, and then, the node position of the B-spline surface is optimized by particle swarm optimization (PSO) to accurately fit the discrete ESST. Based on this, the improved LBL positioning method is constructed. In the underwater positioning test, the effective sound speed can be quickly found by measuring the time of arrival (TOA) of the acoustic signal and the target depth, and moreover, the target position parameters can be quickly and accurately estimated. The numerical simulation results show that the improved positioning method proposed in this paper can effectively improve the LBL positioning accuracy and provide the theoretical basis and the technical support for the underwater navigation and positioning. [ABSTRACT FROM AUTHOR]

Bidirectional controllable propagation of waterborne sound holds significant importance in developing multifunctional underwater acoustic and mechanical devices. However, the existing waterborne acoustic metasurfaces have rarely explored the bidirectional sound modulations. Here, a class of Janus waterborne acoustic metasurface, enabling two‐faced arbitrarily asymmetric wavefront manipulations is reported. A three‐degree‐of‐freedom mechanical system facilitated by acoustic‐structure interaction underwater is proposed to introduce bianisotropic responses of unit cells. Monolayer ultrathin Janus metasurface is inversely designed by utilizing a function‐structure integrated topology optimization framework. Distinct underwater acoustic functionalities, including axial and oblique focusing, beam splitting, and sound diffusion, are successfully demonstrated. Underwater experiments are further conducted to validate the concept of Janus metasurface. The good consistency between experimental and simulated results confirms the excellent two‐faced asymmetric acoustic focusing performance. The proposed Janus metasurface opens up a new dimension for designing advanced waterborne acoustic devices with two‐faced multifunctional wavefront manipulations. [ABSTRACT FROM AUTHOR]

In general, CNN gives the same weight to all position information, which will limit the expression ability of the model. Distinguishing modulation types that are significantly affected by the underwater environment becomes nearly impossible. The transformer attention mechanism is used for the feature aggregation, which can adaptively adjust the weight of feature aggregation according to the relationship between the underwater acoustic signal sequence and the location information. In this paper, a novel aggregation network is designed for the task of automatic modulation identification (AMI) in underwater acoustic communication. It is feasible to integrate the advantages of both CNN and transformer into a single streamlined network, which is productive and fast for signal feature extraction. The transformer overcomes the constraints of sequential signal input, establishing parallel connections between different modulations. Its attention mechanism enhances the modulation recognition by prioritizing the key information. Within the transformer network, the proposed network is strategically incorporated to form a spatial–temporal structure. This structure contributes to improved classification results, and it can obtain more deep features of underwater acoustic signals, particularly at lower signal-to-noise ratios (SNRs). The experiment results achieve an average of 89.4% at −4 dB ≤ SNR ≤ 0 dB, which exceeds other state-of-the-art neural networks. [ABSTRACT FROM AUTHOR]

This paper describes an unusual underwater biological chorus recorded in the Southern California Bight and presents a numerical modeling approach that replicates aspects of the chorus. During one experiment, the evolution of the directionality of the chorusing region over time is suggestive of "The Wave", the human waves performed by fans periodically standing and sitting in sports stadia around the world; here, the region of chorusing periodically propagated upcoast over 20 km of coastline at nearly 1.5 km/s. The chorus occurs predominantly at night in spring and summer, mostly in very shallow waters near the coast. It increases the underwater sound field levels within chorusing regions by 20-30 dB in the 50 Hz to 1 kHz frequency band. The chorus is composed of three parts; 1) a "sunset chorus" which is a 20-to-30 min continuous roar around sunset with received spectral levels up to 100 dB re 1 µPa²/Hz, 2) a "sunrise chorus" of lower level than the sunset chorus, and 3) an all-night-long cycling chorus. The cycling portion is made up of 15-to-20 s periods of higher received spectral levels (up to 90 dB re 1 µPa²/Hz within the chorusing region) each followed by a 10-to-20 s lull in which the spectral levels drop by 4-10 dB. This alternating pattern repeats every 30-40 s throughout the night. The numerical modeling approach is based on the physics of excitable media. A cellular automaton is used to model the two-dimensional spatial grid occupied by the calling animals (units), with each unit being either in the "resting", "excitable", or "active (calling)" state at each time step. Transition from resting to excitable and from active back to resting occurs automatically after a fixed period of time in the present state, whereas the probability of transitioning from excitable to active is determined not only by the elapsed time since entering the excitable state, but also by the received sound level at the unit location, creating a non-linear acoustics-based coupling between units. With appropriate inputs, many determined from measurements of the chorus properties and the individual animal calls themselves, simulations with the model can replicate the cycling levels in the night-long chorus, the continuous din of the sunset chorus, and (once properly initialized) the periodic upcoast evolution of the chorusing region ("The Wave"). When noise from a transiting ship is included in the simulations, the spatiotemporal characteristics of the chorus change appreciably, in ways similar to changes observed during the experiment. [ABSTRACT FROM AUTHOR]

A number of previous papers have used the coupled-mode method to assess three-dimensional scattering by cylindrically symmetric anomalies (seamounts, hills) or anomalies which are invariant in a horizontal direction (wedges, ridges). This paper makes an extension to combinations of these two anomaly types. The upper and lower depth boundaries of the anomalies may be flat or irregular, and the sound source may be anywhere in the medium. After a discretization of the anomalies of the two types with laterally homogeneous rings and strips, respectively, an adaptation of the coupled-mode method yields the solution of the pertinent Helmholtz equation. The adaptation involves a combination of Fourier-series summations to handle the ring anomalies and adaptive wavenumber integrations to handle the strip structure. For each anomaly, recursively computed reflection matrices relate the expansion coefficients for incoming and outgoing normal modes. Iterative solution of a linear equation system for the amplitudes of the scattered cylindrical waves from the ring anomalies, involving formulas for transformation between plane and cylindrical waves, yields an expansion of the field. Related expansions allow isolation of partial waves, multiply scattered among the anomalies. The paper includes examples from underwater acoustics and atmospheric acoustics. [ABSTRACT FROM AUTHOR]

We propose a design of a tunable superior absorber based on the resonance absorption in underwater acoustic metastructure with nested hexagonal tracks. The structure comprises 37 hexagonal-shaped cells formed by two models depending on the formula for hexagonal numbers. Model I is labyrinthine acoustic metastructure (LAM), and model II is labyrinthine acoustic metastructure with a coil-up channel (LAMC). The results of model II demonstrate the achievement of a highly efficient sound absorber, with a maximum value of 0.999, within the frequency range of 130 Hz by rotating the third aperture at an angle of 180°. The effect of dissipative loss could be achieved by carefully controlling nested hexagonal tracks to achieve perfect absorption. Our research on tunable acoustic metastructure with absorbing properties has significant implications for engineering applications, particularly in noise mitigation. Our findings demonstrate the potential of these metastructures to provide tunable functionality, high efficiency, perfect absorption, and ease of construction, all within a compact design. [ABSTRACT FROM AUTHOR]

The extraction of typical features of underwater target signals and excellent recognition algorithms are the keys to achieving underwater acoustic target recognition of divers. This paper proposes a feature extraction method for diver signals: frequency−domain multi−sub−band energy (FMSE), aiming to achieve accurate recognition of diver underwater acoustic targets by passive sonar. The impact of the presence or absence of targets, different numbers of targets, different signal−to−noise ratios, and different detection distances on this method was studied based on experimental data under different conditions, such as water pools and lakes. It was found that the FMSE method has the best robustness and performance compared with two other signal feature extraction methods: mel frequency cepstral coefficient filtering and gammatone frequency cepstral coefficient filtering. Combined with the commonly used recognition algorithm of support vector machines, the FMSE method can achieve a comprehensive recognition accuracy of over 94% for frogman underwater acoustic targets. This indicates that the FMSE method is suitable for underwater acoustic recognition of diver targets. [ABSTRACT FROM AUTHOR]

Chiral metamaterials have been proven to possess many appealing mechanical phenomena, such as negative Poisson's ratio, high-impact resistance, and energy absorption. This work extends the applications of chiral metamaterials to underwater sound insulation. Various chiral metamaterials with low acoustic impedance and proper stiffness are inversely designed using the topology optimization scheme. Low acoustic impedance enables the metamaterials to have a high and broadband sound transmission loss (STL), while proper stiffness guarantees its robust acoustic performance under a hydrostatic pressure. As proof-of-concept demonstrations, two specimens are fabricated and tested in a water-filled impedance tube. Experimental results show that, on average, over 95% incident sound energy can be isolated by the specimens in a broad frequency range from 1 kHz to 5 kHz, while the sound insulation performance keeps stable under a certain hydrostatic pressure. This work may provide new insights for chiral metamaterials into the underwater applications with sound insulation. [ABSTRACT FROM AUTHOR]

The model manifold, an information geometry tool, is a geometric representation of a model that can quantify the expected information content of modeling parameters. For a normal-mode sound propagation model in a shallow ocean environment, transmission loss (TL) is calculated for a vertical line array and model manifolds are constructed for both absolute and relative TL. For the example presented in this paper, relative TL yields more compact model manifolds with seabed environments that are less statistically distinguishable than manifolds of absolute TL. This example illustrates how model manifolds can be used to improve experimental design for inverse problems. [ABSTRACT FROM AUTHOR]

In the marine environment, many animals use sound to interact and communicate with their conspecifics or other species. Over the last decades, the development of sound recording systems has allowed a significant advance in our knowledge of sound production in marine animals. We deployed miniature sound and movement tags on Antarctic fur seals (AFS), a small otariid foraging on mesopelagic fish, to uncover potential underwater vocalizations in this species. Tags recorded underwater sounds synchronously with high‐resolution AFS movements and diving behavior, allowing us to investigate the behavioral context of vocalizations in the natural environment. We provide evidence of underwater vocalizations in foraging female AFS in a context of foraging at sea. AFS produced stereotyped calls made of low‐frequency pulses produced in series, exclusively during foraging dives. We hypothesized that these acoustic pulse series could be used as an acoustic lure to confuse or attract fish prey, however, a larger sample size is needed to study the adaptive significance of these underwater vocalizations. [ABSTRACT FROM AUTHOR]

Dedicated coating materials for anechoism and furtivity in underwater acoustics must exhibit a strong reliability regarding their mechanical resistance to hydrostatic pressure. Soft porous materials, especially, a distribution of soft porous beads within a polyurethane matrix, have been previously proposed as an acoustic insulator device. The purpose of the present letter is to investigate the attenuation efficiency of soft porous silicone beads-based materials while being exposed to uniaxial loads mimicking hydrostatic pressures encountered in underwater acoustics. The acoustic performance of this locally resonant material is then compared to the classical coating technology using micro-balloons. The use of an adapted surfactant (a silicone alkyl polyether compound) in the fabrication process of the soft porous silicone-based beads, obtained through an emulsion templating process, leads to particles exhibiting an open porosity. The (resonant) attenuation of the soft porous beads-based material remains greater than the micro-balloons-based material until several bars. Above this critical resilience value, the mechanical stress irreversibly damages the soft porous beads. [ABSTRACT FROM AUTHOR]

Underwater electric wire explosion (UEWE) has great potential as a shockwave source for medical and industrial applications. This paper focuses on the process of the sub-millisecond underwater electrical wire explosion (smUEWE). The study compared the smUEWE and the microsecond underwater electrical wire explosion, which revealed the occurrence of partial vaporization under smUEWE, leading to the formation of bamboo-shaped cavities and frontal shock waves. The experiments of smUEWE were carried out under different stored energy, the results indicated the plasma shrinkage and cavity separation during the overall ionization process. Additionally, the study observed secondary breakdown caused by the uneven distribution of ionization products. An analysis was conducted on smUEWE considering partial vaporization, which divided the electrical explosion into a positive feedback process which promoted the axial instability and a negative feedback process which formed the uniform plasma channel. The analysis results was consistent with the experimental results. [ABSTRACT FROM AUTHOR]

Abstract Multibeam imaging SONARs have been used for a range of measurement applications, such as measurements of fish lengths. This study aimed to quantify the accuracy of imaging SONAR systems, that varied in frequency and beam geometry, to measure the length of synthetic targets positioned perpendicularly. Blueprint Oculus imaging SONAR systems, with four different (centre) frequencies (750 kHz, 1.2 MHz, 2.1 MHz and 3 MHz), were used to measure the length of three targets of nominal lengths: 10 cm, 20 cm and at ranges between 1 and 15.5 m. The effect of beam geometry on measurement error was then examined using regression analysis. This study found that there was an overestimation of the actual length of the target for all measurements that was inversely proportional to the horizontal beamwidth. The measurement error can be reduced by normalising for beamwidth. However, the variation of measurements (i.e. the precision) was found to also increase with range, which was attributed to the increasing beam separation. It is important that the effect of beamwidth on the accuracy of target length measurements, by imaging SONARs is acknowledged in future studies. One approach to mitigating this problem, is to limit the range at which length measurements are made to a beamwidth that produces an estimated level of error that is acceptable for that study.

In recent years, underwater wireless ultrasonic energy transmission technology (UWUET) has attracted much attention because it utilizes the propagation characteristics of ultrasound in water. Effectively evaluating the performance of underwater ultrasonic wireless energy transmission is a key issue in engineering design. The current approach to performance evaluation is usually based on the system energy transfer efficiency as the main criterion, but this criterion mainly considers the overall energy conversion efficiency between the transmitting end and the receiving end, without an in-depth analysis of the characteristics of the distribution of the underwater acoustic field and the energy loss that occurs during the propagation of acoustic waves. In addition, existing methods focusing on acoustic field analysis tend to concentrate on a single parameter, ignoring the dynamic distribution of acoustic energy in complex aquatic environments, as well as the effects of changes in the underwater environment on acoustic propagation, such as spatial variability in temperature and salinity. These limitations reduce the usefulness and accuracy of models in complex marine environments, which in turn reduces the efficiency of acoustic energy management and optimization. To solve these problems, this study proposes a method to evaluate the performance of underwater ultrasonic energy radiation based on the spatial distribution characteristics of acoustic power. By establishing an acoustic power distribution model in a complex impedance–density aqueous medium and combining numerical simulation and experimental validation, this paper explores the spatial variation of acoustic power and its impact on the energy transfer efficiency in depth. Using high-resolution spatial distribution data and actual environmental parameters, the method significantly improves the accuracy of the assessment and the adaptability of the model in complex underwater environments. The results show that, compared with the traditional method, this method performs better in terms of the accuracy of the acoustic energy radiation calculation results, and is able to reflect the energy distribution and spatial heterogeneity of the acoustic source more comprehensively, which provides an important theoretical basis and practical guidance for the optimal design and performance enhancement of the underwater ultrasonic wireless energy transmission system. [ABSTRACT FROM AUTHOR]

In order to fulfill the practical application demands of precisely localizing underwater vehicles using passive electric field localization technology, we propose a scalar-potential-based method for the passive electric field localization of underwater vehicles. This method is grounded on an intelligent differential evolution algorithm and is particularly suited for use in three-layer and stratified oceanic environments. Firstly, based on the potential distribution law of constant current elements in a three-layer parallel stratified ocean environment, the mathematical positioning model is established using the mirror method. Secondly, the differential evolution (DE) algorithm is enhanced with a parameter-adaptive strategy and a boundary mutation processing mechanism to optimize the key objective function in the positioning problem. Additionally, the simulation experiments of the current element in the layered model prove the effectiveness of the proposed positioning method and show that it has no special requirements for the sensor measurement array, but the large range and moderate number of sensors are beneficial to improve the positioning effect. Finally, the laboratory experiments on the positioning method proposed in this paper, involving underwater simulated current elements and underwater vehicle tracks, were carried out successfully. The results indicate that the positioning method proposed in this paper can achieve the performance requirements of independent initial value, strong anti-noise capabilities, rapid positioning speed, easy implementation, and suitability in shallow sea environments. These findings suggest a promising practical application potential for the proposed method. [ABSTRACT FROM AUTHOR]

Optical properties of afterglow luminescent particles (ALPs) in mechanoluminescence (ML) and mechanical quenching (MQ) have attracted great attention for diverse technological applications. However, these unique phenomena need to be more clearly explained for the specific photonic application. Here, ALPs are designed for the development of a wearable and rewritable photonic display system as a communication toolbox under dark conditions or underwater environments with limited communication. This display system demonstrates long‐lasting MQ after short ML along the handwritten trajectories with mechanical pressure and the written content can be easily erased by short UV light irradiation, preserving the system integrity with the high reproducibility of ML and MQ responses. The effect of trapped electrons and the recharging process on the ML and MQ is assessed, which provides insights into their underlying mechanisms. In addition, this display system exhibits remarkable resistance to humidity and retains its rewritable and photonic capabilities underwater for a long‐term period. Furthermore, the rewritable property of display system on human skin is demonstrated, confirming their effectiveness as a wearable photonic display system. Taken together, this research will pave a big new avenue to develop biophotonic materials for various biomedical applications with mechano‐optical conversions. [ABSTRACT FROM AUTHOR]

Accurate whistle contour extraction is crucial in many dolphin behavioural studies. Traditionally, whistle contour extraction involves a first step of finding whistle candidates by peak-level detection in the time-frequency domain, followed by a determination of when peaks are close enough to each other to be part of the same whistle contour. In complex scenarios, such as those with a large number of individuals vocalising simultaneously or those with a sudden increase in background noise, peak-level detection may not provide a number of accurate whistle candidates that is large enough to extract the whistle contour or to disambiguate individual whistles when they cross one another. In these adverse scenarios, a different approach, based on the pyknogram representation, can produce a more accurate detection of whistle candidates and evenly distributed candidates throughout the duration of the whistle. This work compares the peak-level extraction approach of the spectrogram with the point-density extraction approach of the pyknogram. We propose a technique that combines estimates of the central frequency and bandwidth to extract whistle candidates in adverse scenarios. The method has been successfully used for the vocalisation extraction of dolphins in the Bay of Biscay (Spain) using a database of more than 2000 dolphin whistles. [ABSTRACT FROM AUTHOR]

A small set of pilots in underwater acoustics OFDM (UWA-OFDM) systems tends to be insufficient for recovering the channel impulse response (CIR). This may result from the fast changes in the propagation environment and the requirement for high transmission data rates. A previous work, namely PE, considered the received subcarriers whose distances to their closest constellation points below the predetermined threshold T as potential pilots. However, extracting these pilots at the same time gives no chance to use some of them to facilitate searching for others. Fixing threshold T is also another limitation for searching pilot candidates. This paper proposes a reliable pilot search (RPS) method that consists of a multi-iterations pilot searching process with an adaptive threshold T a to improve the estimator in UWA-OFDM. The pilot search process gradually extracts reliable pilots at each iteration based on the threshold T a and evaluates them by performing channel estimation. Our method is compared to the MMSE and PE estimators on a wide range of settings, including the number of channel taps, pilot spacing, and various modulation schemes (i.e., MPSK and MQAM). The experimental results show that the RPS method often outperforms the MMSE and PE methods in terms of bit error rate (BER). [ABSTRACT FROM AUTHOR]

The article performs a comparative analysis of the underwater sounds of two sympatric dolphin species living in the Black Sea: bottlenose and common dolphins. During sound processing and analysis, the special program nanoCAD 22 was used. Both the similarity of the physical parameters of the sounds of the two species and a number of specific features of whistles characteristic of each were demonstrated. Common dolphin production of some types of whistles with significant similarities (sometimes almost identical) to the signature whistles of bottlenose dolphins was detected and analyzed. [ABSTRACT FROM AUTHOR]

Passive detection of target-of-interest (TOI) within strong interferences poses a challenge. This paper introduces an adaptive interference suppression based on an invariant subspace of matrix matching. Assume that the TOI-bearing intervals are known. We define a correlation ratio for each eigenvector to obtain the highest one. Then, we use invariant subspace of matrix matching to measure the distance between two invariant projection matrices of this eigenvector. This identifies and removes the eigenvectors associated with TOI. Finally, the remaining eigenvectors are subtracted from the sample covariance matrix to suppress interference and noise. The viability of the proposed method is demonstrated experimentally. [ABSTRACT FROM AUTHOR]

An underwater acoustic recorder was moored off Heard Island from September 2017 through March 2018 to listen for marine mammals. Analysis of data was initially conducted by visual inspection of long-term spectral averages to reveal sounds from sperm whales, Antarctic and pygmy blue whales, fin whales, minke whales, odontocete whistles, and noise from nearby ships. Automated detection of sperm whale clicks revealed they were seldom detected from September through January (n = 35 h) but were detected nearly every day of February and March (n = 684 h). Additional analysis of these detections revealed further diel and demographic patterns. [ABSTRACT FROM AUTHOR]

In this work, the performance of coded continuous phase modulation (CPM) transceivers for orthogonal frequency-division multiplexing (OFDM) in underwater acoustic channels is evaluated. The proposed technique employs the Bose–Chaudhuri–Hocquenghem (BCH) class of cyclic codes, and a CPM-based mapper is being used in place of a traditional OFDM mapper. Bit-error-rates (BERs) for various distances are evaluated. We use the Bellhop acoustic channel simulator that is considered to be very close to a real underwater channel. The performance of the proposed system is evaluated for 23 values of the CPM modulation index h as a function of the distance between the transmitter (Tx) and receiver (Rx). Based upon the error performance, we identified several best-performing CPM indices. We also observed that for Tx–Rx distances of 100 and 250 m, the proposed system gives acceptable performance without the need for equalization. We also compared the out-of-band radiation of the proposed system with PSK-OFDM and observed that the uncoded CPM-OFDM has a better out-of-band (OOB) performance than the traditional OFDM. Moreover, a comparison of BERs with the traditional PSK-OFDM system shows that the proposed system outperforms the traditional OFDM system by a wide margin. [ABSTRACT FROM AUTHOR]

Active sonar can usually only directly measure the distance and bearing information of underwater targets, and cannot directly obtain target velocity, acceleration and other information. Therefore, the amount of information is relatively small, making it difficult to support the construction of complex motion models. At the same time, the motion state of underwater maneuvering targets is changeable. In response to the problem of detecting and tracking underwater moving targets by active sonar, this paper proposes a target transient model correction (TMC) filtering tracking method. Based on the conventional Kalman filter (KF) estimation, residual covariance is used as a signal quantity. When there is a large change in it, a transient filter with constant gain is adopted to filter the measurement value. The filtered output is used to correct the KF gain matrix and the target motion state model, to avoid the problem of increasing or even diverging KF estimation errors caused by changes in process noise. Using this method can solve the problem of maintaining stability and filtering estimation accuracy of active sonar tracking of underwater maneuvering targets with less computational and engineering costs. [ABSTRACT FROM AUTHOR]

A wave glider is an ocean observation platform that utilizes wave energy to drive and solar energy to power. Its metal structure will generate related electromagnetic fields due to corrosion and underwater motion. In the detection of weak electromagnetic field signals underwater, its own electromagnetic field characteristics will have an impact on signal detection. To study the applicability of electric field sensors and magnetic field sensors on wave glider platforms, the structural characteristics of the wave glider were analyzed, and the installation positions of electric field sensors and magnetic field sensors were designed based on the different motion states of the water surface mother body and underwater towing body. The measured electromagnetic field data of the wave glider platform were measured, and the measured data were analyzed. It was determined that the interference electric field energy under typical working conditions of the wave glider was mainly concentrated within 1 Hz, which decreased with increasing frequency, and the magnitude was mV/m. The magnitude of the interference magnetic field is several tens of nT, indicating that the electromagnetic field interference is significant during the working state of the wave glider. Installing an electric field sensor directly at the bottom of the wave glider will cause significant noise interference, while installing the magnetic field sensor directly at the bottom of the tractor will affect the servo and the shaking-induced magnetic field. Moreover, wave gliders should not use electric field signals below 1 Hz as signal sources, but they can utilize axial frequency electromagnetic fields to detect weak electromagnetic signals underwater. [ABSTRACT FROM AUTHOR]

The spatial-temporal distribution of underwater sound speed plays a critical role in determining the propagation mode of underwater acoustic signals. Therefore, rapid estimation and prediction of sound speed distribution are imperative for facilitating underwater positioning, navigation, and timing (PNT) services. While sound speed profile (SSP) inversion methods offer quicker response times compared to direct measurement methods, these methods often focus on constructing spatial sound velocity fields and heavily rely on sonar observation data, thus imposing stringent requirements on data sources. To delve into the temporal distribution pattern of sound speed and achieve SSP prediction without relying on sonar observation data, we introduce the hierarchical long short-term memory (H-LSTM) neural network for SSP prediction. Our method enables the estimation of sound speed distribution without the need for on-site data measurement, significantly enhancing time efficiency. Compared to other state-of-the-art approaches, the H-LSTM model achieves a root mean square error (RMSE) of less than 1 m/s in predicting monthly average sound speed distribution. Its prediction accuracy has improved several-fold over alternative methods, which validates the robust capability of our proposed model in predicting SSP. [ABSTRACT FROM AUTHOR]

In the field of underwater acoustics, the signal-to-noise ratio (SNR) is generally low, and the underwater environment is complex and variable, making target azimuth estimation highly challenging. Traditional model-based subspace methods exhibit significant performance degradation when dealing with coherent sources, low SNR, and small snapshot data. To overcome these limitations, an improved model based on SubspaceNet, called PConv-GAM Residual SubspaceNet (PGR-SubspaceNet), is proposed. This model embeds the global attention mechanism (GAM) into residual blocks that fuse PConv convolution, making it possible to capture richer cross-channel and positional information. This enhancement helps the model learn signal features in complex underwater conditions. Simulation results demonstrate that the underwater target azimuth estimation method based on PGR-SubspaceNet exhibits lower root mean square periodic error (RMSPE) values when handling different numbers of narrowband coherent sources. Under low SNR and limited snapshot conditions, its RMSPE values are significantly better than those of traditional methods and SubspaceNet-based enhanced subspace methods. PGR-SubspaceNet extracts more features, further improving the accuracy of direction-of-arrival estimation. Preliminary experiments in a pool validate the effectiveness and feasibility of the underwater target azimuth estimation method based on PGR-SubspaceNet. [ABSTRACT FROM AUTHOR]

The advancement of underwater cognitive acoustic network (UCAN) technology aims to improve spectral efficiency and ensure coexistence with the underwater ecosystem. As the demand for short-term underwater applications operated under distributed topologies, like autonomous underwater vehicle cluster operations, continues to grow, this paper presents Underwater Multi-channel Medium Access Control with Cognitive Acoustics (UMMAC-CA) as a suitable channel access protocol for distributed UCANs. UMMAC-CA operates on a per-frame basis, similar to the Multi-channel Medium Access Control with Cognitive Radios (MMAC-CR) designed for distributed cognitive radio networks, but with notable differences. It employs a pre-determined data transmission matrix to allow all nodes to access the channel without contention, thus reducing the channel access overhead. In addition, to mitigate the communication failures caused by randomly occurring interferers, UMMAC-CA allocates at least 50% of frame time for interferer sensing. This is possible because of the fixed data transmission scheduling, which allows other nodes to sense for interferers simultaneously while a specific node is transmitting data. Simulation results demonstrate that UMMAC-CA outperforms MMAC-CR across various metrics, including those of the sensing time rate, controlling time rate, and throughput. In addition, except for in the case where the data transmission time coefficient equals 1, the message overhead performance of UMMAC-CA is also superior to that of MMAC-CR. These results underscore the suitability of UMMAC-CA for use in challenging underwater applications requiring multi-channel cognitive communication within a distributed network architecture. [ABSTRACT FROM AUTHOR]

Studying marine soundscapes by detecting known sound events and quantifying their spatio-temporal patterns can provide ecologically relevant information. However, the exploration of underwater sound data to find and identify possible sound events of interest can be highly time-intensive for human analysts. To speed up this process, we propose a novel methodology that first detects all the potentially relevant acoustic events and then clusters them in an unsupervised way prior to manual revision. We demonstrate its applicability on a short deployment. To detect acoustic events, a deep learning object detection algorithm from computer vision (YOLOv8) is re-trained to detect any (short) acoustic event. This is done by converting the audio to spectrograms using sliding windows longer than the expected sound events of interest. The model detects any event present on that window and provides their time and frequency limits. With this approach, multiple events happening simultaneously can be detected. To further explore the possibilities to limit the human input needed to create the annotations to train the model, we propose an active learning approach to select the most informative audio files in an iterative manner for subsequent manual annotation. The obtained detection models are trained and tested on a dataset from the Belgian Part of the North Sea, and then further evaluated for robustness on a freshwater dataset from major European rivers. The proposed active learning approach outperforms the random selection of files, both in the marine and the freshwater datasets. Once the events are detected, they are converted to an embedded feature space using the BioLingual model, which is trained to classify different (biological) sounds. The obtained representations are then clustered in an unsupervised way, obtaining different sound classes. These classes are then manually revised. This method can be applied to unseen data as a tool to help bioacousticians identify recurrent sounds and save time when studying their spatio-temporal patterns. This reduces the time researchers need to go through long acoustic recordings and allows to conduct a more targeted analysis. It also provides a framework to monitor soundscapes regardless of whether the sound sources are known or not. [ABSTRACT FROM AUTHOR]

Directional sensing of underwater acoustic signals is vital in many areas, such as waterborne navigation systems, abyssal signal communication, and underwater sound source localization. Here, we propose an easy-to-make acoustic sensing metamaterial device, which is made of a bubble architecture with a line defect. Both numerical and experimental demonstrations show that an input-direction-sensitive response with an acoustic pressure enhancement factor ~ 13.9 was achieved approximately at the resonant frequency. Furthermore, enhanced waterborne acoustic sensing at different frequencies was realized by adjusting the volume of the defect cavity. This strategy provides an effective and feasible method for underwater weak signal detection and localization. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite System—Acoustic ranging combination technique (GNSS-A) is a seafloor geodetic observation technique that achieves an accuracy of centimetres by combining high-rate GNSS data with acoustic ranging. The technique determines the seafloor position by acoustic ranging between the sea surface and multiple seafloor stations, using GNSS data from the sea surface station. Here, the gradient state of the underwater sound speed structure (SSS) is a significant source of error. The open-source software GARPOS can reduce the effect from underwater gradient structures by retrieving the underwater disturbance as a parameter projected onto the sea surface and seafloor. To evaluate the effects of underwater disturbances, a quantitative comparison of the model parameters is necessary. In this study, we developed a representation method to evaluate features of the ocean field. Here, the expression method was described in the order of a formulation and an interpretation in the case of a 2-D cross-section and extension to the case of an actual 3-D field. This method makes it possible to evaluate SSS states in the GNSS-A observations. As an example, we showed the correlation between the anomaly of the expressed ocean state and the anomaly of the seafloor station position, showing that this expression method is an effective index for correcting bias errors. Additionally, we used the data from sites located in the Kuroshio area, a strong current near Japan, to show that the ocean state can be quantitatively interpreted using this expression method. [ABSTRACT FROM AUTHOR]

The probability distribution of three-dimensional sound speed fields (3D SSFs) in an ocean region encapsulates vital information about their variations, serving as valuable data-driven priors for SSF inversion tasks. However, learning such a distribution is challenging due to the high dimensionality and complexity of 3D SSFs. To tackle this challenge, we propose employing the diffusion model, a cutting-edge deep generative model that has showcased remarkable performance in diverse domains, including image and audio processing. Nonetheless, applying this approach to 3D ocean SSFs encounters two primary hurdles. First, the lack of publicly available well-crafted 3D SSF datasets impedes training and evaluation. Second, 3D SSF data consist of multiple 2D layers with varying variances, which can lead to uneven denoising during the reverse process. To surmount these obstacles, we introduce a novel 3D SSF dataset called 3DSSF, specifically designed for training and evaluating deep generative models. In addition, we devise a high-capacity neural architecture for the diffusion model to effectively handle variations in 3D sound speeds. Furthermore, we employ state-of-the-art continuous-time-based optimization method and predictor-corrector scheme for high-performance training and sampling. Notably, this paper presents the first evaluation of the diffusion model's effectiveness in generating 3D SSF data. Numerical experiments validate the proposed method's strong ability to learn the underlying data distribution of 3D SSFs, and highlight its effectiveness in assisting SSF inversion tasks and subsequently characterizing the transmission loss of underwater acoustics. [ABSTRACT FROM AUTHOR]

The conversion from seismic to ocean-acoustic waves occurs in different places on the bottom of the ocean, often hundreds to thousands of kilometers away from the epicenter. Here, we investigate this conversion process by studying 15 large-magnitude earthquakes that occurred between 2014 and 2022 along the Kermadec Arc in the southwestern Pacific Ocean. To pinpoint the location where seismic-to-acoustic conversion takes places, we analyze hydroacoustic signals recorded by a hydrophone triplet station of the International Monitoring System in the Juan Fernández archipelago. Results from direction-of-arrival and travel-time calculations indicate that the location of the conversion zone largely matches segments of the Louisville Seamount Chain, its lateral extent ranging from approximately 300 to 1800 km, and its location depending on the geometry between earthquake epicenter and the seamounts. [ABSTRACT FROM AUTHOR]

Sound speed is a critical parameter in ocean acoustic studies, as it determines the propagation and interpretation of recorded sounds. The potential for exploiting oceanic vessel noise as a sound source of opportunity to estimate ocean sound speed profile is investigated. A deep learning-based inversion scheme, relying upon the underwater radiated noise of moving vessels measured by a single hydrophone, is proposed. The dataset used for this study consists of Automatic Identification System data and acoustic recordings of maritime vessels transiting through the Santa Barbara Channel between January 2015 and December 2017. The acoustic recordings and vessel descriptors are used as predictors for regressing sound speed for each meter in the top 200 m of the water column, where sound speeds are most variable. Multiple (typically ranging between 4 and 10) transits were recorded each day; therefore, this dataset provides an opportunity to investigate whether multiple acoustic observations can be leveraged together to improve inversion estimates. The proposed single-transit and multi-transit models resulted in depth-averaged root-mean-square errors of 1.79 and 1.55 m/s, respectively, compared to the seasonal average predictions of 2.80 m/s. [ABSTRACT FROM AUTHOR]

Predicting acoustic transmission loss in the SOFAR channel faces challenges, such as excessively complex algorithms and computationally intensive calculations in classical methods. To address these challenges, a deep learning-based underwater acoustic transmission loss prediction method is proposed. By properly training a U-net-type convolutional neural network, the method can provide an accurate mapping between ray trajectories and the transmission loss over the problem domain. Verifications are performed in a SOFAR channel with Munk's sound speed profile. The results suggest that the method has potential to be used as a fast predicting model without sacrificing accuracy. [ABSTRACT FROM AUTHOR]

Multibeam imaging SONARs have been used for a range of measurement applications, such as measurements of fish lengths. This study aimed to quantify the accuracy of imaging SONAR systems, that varied in frequency and beam geometry, to measure the length of synthetic targets positioned perpendicularly.Blueprint Oculus imaging SONAR systems, with four different (centre) frequencies (750 kHz, 1.2 MHz, 2.1 MHz and 3 MHz), were used to measure the length of three targets of nominal lengths: 10 cm, 20 cm and at ranges between 1 and 15.5 m. The effect of beam geometry on measurement error was then examined using regression analysis.This study found that there was an overestimation of the actual length of the target for all measurements that was inversely proportional to the horizontal beamwidth. The measurement error can be reduced by normalising for beamwidth. However, the variation of measurements (i.e. the precision) was found to also increase with range, which was attributed to the increasing beam separation.It is important that the effect of beamwidth on the accuracy of target length measurements, by imaging SONARs is acknowledged in future studies. One approach to mitigating this problem, is to limit the range at which length measurements are made to a beamwidth that produces an estimated level of error that is acceptable for that study. [ABSTRACT FROM AUTHOR]

Side-scan sonar (SSS) is now a prevalent instrument for large-scale seafloor topography measurements, deployable on an autonomous underwater vehicle (AUV) to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory. However, SSS images often suffer from speckle noise caused by mutual interference between echoes, and limited AUV computational resources further hinder noise suppression. Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge. To address the problem, RepDNet, a novel and effective despeckling convolutional neural network is proposed. RepDNet introduces two re-parameterized blocks: the Pixel Smoothing Block (PSB) and Edge Enhancement Block (EEB), preserving edge information while attenuating speckle noise. During training, PSB and EEB manifest as double-layered multi-branch structures, integrating first-order and secondorder derivatives and smoothing functions. During inference, the branches are re-parameterized into a 3 x 3 convolution, enabling efficient inference without sacrificing accuracy. RepDNet comprises three computational operations: 3 x 3 convolution, element-wise summation and Rectified Linear Unit activation. Evaluations on benchmark datasets, a real SSS dataset and Data collected at Lake Mulan aestablish RepDNet as a well-balanced network, meeting the AUV computational constraints in terms of performance and latency. [ABSTRACT FROM AUTHOR]

We examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s−1 and significant wave heights up to 10 m. Our observations include arrays of freely drifting SWIFT buoys together with shipboard systems, which enabled concurrent high‐resolution measurements of wind, waves, bubble plumes, and turbulence. We estimate bubble plume penetration depth from echograms extending to depths of more than 30 m in a surface‐following reference frame collected by downward‐looking echosounders integrated onboard the buoys. Our observations indicate that mean and maximum bubble plume penetration depths exceed 10 and 30 m beneath the surface during high winds, respectively, with plume residence times of many wave periods. They also establish strong correlations between bubble plume depths and wind speeds, spectral wave steepness, and whitecap coverage. Interestingly, we observe a robust linear correlation between plume depths, when scaled by the total significant wave height, and the inverse of wave age. However, scaled plume depths exhibit non‐monotonic variations with increasing wind speeds. Additionally, we explore the dependencies of the combined observations on various non‐dimensional predictors used for whitecap coverage estimation. This study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing. Plain Language Summary: Quantifying the statistics of bubble plumes generated during ocean surface wave breaking is essential to understanding the exchange between the ocean and the atmosphere. Bubble plumes also cause important variations in underwater acoustics and optics. Recent studies also suggest that the statistics of bubble plumes are skillful predictors for total energy loss during wave breaking, which is an essential quantity for accurate wave forecasting. In this study, we examine how these bubble plume statistics change with different wind and wave conditions, including during storms. We used echosounders on drifting buoys to detect the bubbles and estimate how deep they go in the ocean. We also used shipboard camera systems to measure the surface area of the bubble plumes. We successfully develop multiple empirical relationships that allow us to predict how bubble plume depth and surface area change as a function of simple wind and wave statistics. These statistics are readily available from existing forecast models or typical ocean buoys. Our findings reveal that bubble plume depth is correlated with its visible surface area. This intriguing correlation suggests that we might estimate the volume of bubble plumes simply by observing the ocean surface from above. Key Points: Bubble plumes generated during ocean surface wave breaking are observed with echosounders on drifting buoysBubble plume depths are well correlated with whitecap coverage, wind speed, and spectral wave steepnessBubble plumes persist for many wave periods and exceed the persistence of visible surface foam [ABSTRACT FROM AUTHOR]

To evaluate underwater sound, a simple non-invasive optical technique based on self-interference to detect low-frequency underwater acoustic signals was demonstrated. Clear self-interference fringes of a laser beam reflected from the surface capillary wave transformed from a low-frequency underwater acoustic signal by a cylinder were observed. This study was also aimed at developing an artificial neural network (ANN) model with input from an optical pattern. The relationship between the optical pattern and the frequency of underwater sound was established, and an optimal combination of hyper-parameters was obtained. By analyzing the fringe region and the fringe interval, the frequency of the underwater acoustic signal and its relative amplitude were measured. A model based on physical optics modified the fringe distribution function, and the theoretical fit with the modified function was in good agreement with experimental observation. The BP-ANN model exhibited good performance in establishing the relationship between the optical pattern and underwater sound. [ABSTRACT FROM AUTHOR]

Simulating the acoustic field excited by pulse sound sources holds significant practical value in computational ocean acoustics. Two primary methods exist for modeling underwater acoustic propagation in the time domain: the Fourier synthesis technique based on frequency decomposition and the time-domain underwater acoustic propagation model (TD-UAPM). TD-UAPMs solve the wave equation in the time domain without requiring frequency decomposition, providing a more intuitive explanation of the physical process of sound energy propagation over time. However, time-stepping numerical methods can accumulate numerical errors, making it crucial to improve the algorithm's accuracy for TD-UAPMs. Herein, the time-domain wavenumber integration model SPARC was improved by replacing the second-order finite element method (FEM) with the high-order accuracy finite difference method (FDM). Furthermore, the matched interface and boundary (MIB) method was used to process the seabed more accurately. The improved model was validated using three classic underwater acoustic benchmarks. By comparing the acoustic solutions obtained using the FDM and the FEM, it is evident that the improved model requires fewer grid points while maintaining the same level of accuracy, leading to lower computational costs and faster processing compared to the original model. [ABSTRACT FROM AUTHOR]

When an airborne sound source is in rapid motion, the acoustic signal detected by the underwater sensor experiences a substantial Doppler shift. This shift is intricately linked to the motion parameters of the sound source. Analyzing the Doppler shift characteristics of received acoustic signals enables not only the estimation of target motion parameters but also the localization of the airborne sound source. Currently, the predominant methods for estimating parameters of uniformly moving targets are grounded in classical approaches. In this study, the application of the Doppler warping transform, traditionally applicable to sound sources in uniform linear motion, is extended to encompass a broader spectrum of sound source trajectories. Theoretical and experimental data validate the efficacy of this transform in linearizing the Doppler shift induced by a source in curved motion. Building upon this foundation, a methodology is proposed for locating airborne acoustic sources in curved motion from underwater. Sea experimental data corroborate the method's effectiveness in achieving underwater localization of a helicopter target during curved motion. [ABSTRACT FROM AUTHOR]

A hydrophone is a core component of sonar and plays a significant role in underwater detection. High sensitivity and wide‐frequency responsiveness are crucial parameters for underwater mechanosensors. This study introduces an innovative wood‐based hydrophone for precise detection of water wave spectra and a wide range of underwater sounds. The wood hydrophone consists of a conductive wood electrode with deposited polypyrrole (PPy) microbranches (polypyrrole wood (PW)) and a cellulosic micropatterned anti‐swelling hydrogel (MPASH) serving as the dielectric layer. As pressure increases within the range of 6.4 Pa to 1.2 kPa, the densely distributed PPy microbranches within the wood fiber cell lumina contact with more tips of the self‐wrinkled micropatterns of MPASH. This interaction results in a four‐order‐of‐magnitude increase in capacitance, leading to an unprecedented sensitivity of 1153 kPa−1 toward microstresses. Due to the presence of multisized configurations in both PW and MPASH, the sensitivity of the wood hydrophone decreases gradually (268 kPa−1 up to 37 kPa). The receiving sensitivity of the wood hydrophone for acoustic waves is greater than ‐174 dB within the frequency range of 250–2300 Hz. This work presents a promising avenue for the development of underwater detection devices utilizing graded wood channels and micropatterned cellulosic hydrogels. [ABSTRACT FROM AUTHOR]

Harbor porpoises (Phocoena phocoena) are the only cetaceans routinely sighted in Hood Canal, a narrow fjord that comprises the western edge of Puget Sound, Washington, USA. Harbor porpoises are sensitive to anthropogenic sounds, including noise from recreational and commercial vessel traffic, and the United States Navy, which conducts military training and testing within Hood Canal that can include underwater sound sources. This study was funded as part of the Navy monitoring program to assess potential impacts of naval activities on cetaceans. We conducted vessel-based line-transect surveys for harbor porpoises in Hood Canal in 2022-2023 to derive seasonal estimates of abundance and density. We carried out surveys over 37 days and surveyed the entire canal twice per season totaling 2,176 km of on-effort track line. We recorded 809 oneffort harbor porpoise groups and 1,385 individuals. Seasonal abundance estimates were lowest in winter (308 animals, 95% CI = 189-503) and gradually increased through spring and summer to a peak of 1,336 animals (95% CI = 826-2,160) in fall. Overall porpoise density was highest in central Hood Canal, an area that includes a designated United States Navy training range, though porpoise sightings were notably absent in a 21-km² area adjacent to the naval submarine base within this otherwise high-density region. Though we collected only a single year of data, these results suggest that harbor porpoise abundance in Hood Canal increased significantly since it was last estimated (2013-2015). The notable seasonal fluctuation of harbor porpoise abundance suggests Hood Canal may host a larger percentage of the overall Washington Inland Waters stock during the fall season, raising important management considerations. [ABSTRACT FROM AUTHOR]

To further design and develop broadband and efficient underwater sound absorption structure, we propose a hybrid acoustic structure composed of a rubber matrix layer, cylindrical cavity, pentamode metamaterial (PM) layer, impedance matching layer, and steel backing plate. Thanks to the special properties of the PMs, the hybrid acoustic structure obtains excellent broadband sound absorption performance (SAP) in the frequency range of 500–10000 Hz than that of the traditional cavity acoustic structure. To this end, we study the design principle of PM structure and its metal–water characteristics and analyze the sound absorption mechanism at the working frequency. In addition, the research shows that the material and geometric parameters of the structure have a significant impact on the SAP. By the optimization of structural material parameters, the average absorption coefficient at 500–10000 Hz can further increase to above 0.781. Finally, we also demonstrate that the structure still has good SAP under a wide range of oblique incidence angles. The research in this paper opens up bright perspectives for the design of underwater anechoic coatings for multifunctional applications. [ABSTRACT FROM AUTHOR]

As the global effects of climate change become more known year by year, it becomes ever-more pertinent to examine the effects this may bring for every aspect of modern life we rely on. One topic of focus is that of multi-frequency sonar communication and navigational systems, which rely on well-established relationships relating to wave speed, signal intensity, and attenuation. We compiled data on oceanic temperature, acidity, and salinity in the Upper European Shelf, which includes the North Sea and Mediterranean Sea, from 2006 to 2072 using the CMIP5 future climate model in the RCP8.5 scenario. We calculate that the speed of sound in the northern European oceanic area will decrease by almost 18 m/s by 2072, with an average yearly decrease in sound speed by 0.37 m/s. The attenuation of sound through water will change year by year, calculated based on a higher-order polynomial regression dependent on the frequency of sonar used. The maximum operating ranges of active low-frequency, mid-frequency, and high-frequency sonar systems would theoretically change by +0.06%, -0.19%, and +0.71%, respectively per year, if no other factors are affected. Due to increased sound propagation, the ambient noise level of the ocean would also increase and have some counter-effect to the increased detection range however that increase in noise level was not quantitatively analyzed in this study. [ABSTRACT FROM AUTHOR]

An algorithm has been substantiated for passive determining the distance to sound sources in convergence zones (CZ), which are observed in most deep-sea areas of the World Ocean. The algorithm is based on the well-known pattern of formation of the ray structure of the acoustic field of the source signal at the input of the receiving array in CZ. The pattern is as follows: when a source enters a CZ by crossing its near boundary, the maximum energy of its signal arrives at the array along rays with negative grazing angles, and when the source enters a CZ by crossing its far boundary, along rays with positive grazing angles. The accuracy in determining distance using the proposed algorithm for detecting surface and underwater sources is assessed. [ABSTRACT FROM AUTHOR]

On the example of an underwater sound channel typical of the Philippine Sea [1–3], it was established by numerical simulation using mode theory that during experimental studies of the propagation of explosive signals by R.A. Vadov [1–3], manifestation of a weakly divergent beam in the spatiotemporal structure of the acoustic field was observed for the first time: at certain locations of the corresponding points in the oceanic waveguide, in addition to classical quadruples of pulses, additional acoustic signals with small time delays with respect to them. [ABSTRACT FROM AUTHOR]