Underwater Acoustic Measurements Research Articles

Study on the Ensuring of Reliability and Repeatability of Research in the Area of Marine Ecology through Calibration of Underwater Acoustics Devices

This paper emphasizes the crucial needs and reasons to ensure the reliability and repeatability of underwater acoustic measurements. As an exemplification of the aforementioned acoustic measurements challenges, the development of metrological infrastructure in the area of underwater acoustics in GUM (Central Office of Measures, Poland) is presented. An analysis of presented solutions was carried out mainly in the low frequency range, in comparison with other solutions recently developed worldwide. Moreover, factors influencing the sensitivity of hydroacoustic measuring devices are discussed. The summary of this discussion outlines the further works aimed at ensuring the reliability and repeatability of underwater acoustic measurements. The conclusions present the current state of the calibration infrastructure of underwater acoustic devices, with particular emphasis on marine ecology and fisheries sciences.

Deep-Learning-Based detection of recreational vessels in an estuarine soundscape in the May River, South Carolina, USA.

This paper presents a deep-learning-based method to detect recreational vessels. The method takes advantage of existing underwater acoustic measurements from an Estuarine Soundscape Observatory Network based in the estuaries of South Carolina (SC), USA. The detection method is a two-step searching method, called Deep Scanning (DS), which includes a time-domain energy analysis and a frequency-domain spectrum analysis. In the time domain, acoustic signals with higher energy, measured by sound pressure level (SPL), are labeled for the potential existence of moving vessels. In the frequency domain, the labeled acoustic signals are examined against a predefined training dataset using a neural network. This research builds training data using diverse vessel sound features obtained from real measurements, with a duration between 5.0 seconds and 7.5 seconds and a frequency between 800 Hz to 10,000 Hz. The proposed method was then evaluated using all acoustic data in the years 2017, 2018, and 2021, respectively; a total of approximately 171,262 2-minute.wav files at three deployed locations in May River, SC. The DS detections were compared to human-observed detections for each audio file and results showed the method was able to classify the existence of vessels, with an average accuracy of around 99.0%.

Characterizing the absolute sound levels of ambient noise in a water tank

The underwater acoustic measurement tank used at Brigham Young University is affected by several external sound sources which, although easily identified or hypothesized about on a superficial level, must be investigated in order to determine their specific effects on data collection. Therefore, our goal is to characterize the absolute sound levels of these external acoustic sources. The measurements are conducted using B&K and TC4038 hydrophones. Data are collected over frequency bands within the “flat” range of these hydrophones, facilitating the consistent identification of ambient sounds across several bands. Measurements are taken at various points of the tank in order to determine to what extent tank location affects the ambient sound. Data in Volts are converted to Pascals by applying sensitivity values. To evaluate the accuracy of levels obtained, the same method is applied to the signal from a known source and compared to the levels obtained via a deconvolution approach. The conclusions of this study are applicable in obtaining sound levels in our own tank and in other environments (e.g., aquariums). [Undergraduate Research supported by the College of Physical and Mathematical Sciences, Brigham Young University]

Robust Positioning Estimation for Underwater Acoustics Targets with Use of Multi-Particle Swarm Optimization

With the extensive application of sensor technology in scientific ocean research, ocean resource exploration, underwater engineering construction, and other fields, underwater target positioning technology has become an important support for the ocean field. This paper proposes a robust positioning algorithm that combines the disadvantages of distributed estimation and particle swarm optimization, which can solve the large localization error problem caused by uncertainties in underwater acoustic communication and sampling processes. Considering the presence of ranging anomalies and sampling packet loss in underwater acoustic measurements, a weighted coupling filling method is used to correct the outliers in an underwater acoustic ranging signal. Based on the mapping model from the element array to the underwater acoustic responder, an unconstrained optimization algorithm for one-time localization estimation of underwater acoustic targets was established. Based on the one-time localization estimation results of underwater acoustic targets, an improved multi-particle swarm optimization estimation based on interactive search is proposed, which improves the accuracy of underwater target localization. The numerical results show that the positioning accuracy of the proposed algorithm can be effectively enhanced in cases of distance measurement errors and azimuth measurement errors. Compared with the positioning error before optimization, the positioning error can be reduced after optimization. Additionally, the experiment was carried out in the underwater environment of Hangzhou Qiandao Lake, which verified the positioning performance of the proposed algorithm.

Micromachined piezoelectric sensor with radial polarization for enhancing underwater acoustic measurement

This work presents an underwater acoustic sensor featuring a radial polarized piezoelectric diaphragm, which aims to work in d33 mode to enhance its performance. For the sake of accomplishing the in-plane polarization, interdigital electrodes based on semi-circular ring patterns are designed on both sides and aligned along the thickness direction of the diaphragm. Effects of electrode parameters on the polarization orientation are numerically analyzed by the conversion relationship between different coordinates. Using the Kirchhoff plate theory and Rayleigh-Ritz method, a mathematical model is developed to investigate the dynamic properties of the sensor. The results indicate that the output voltages increase with the increase of the electrode inner radius, width, and spacing but decrease with the increase of the diaphragm thickness and radius. Sensor prototypes are fabricated by the microelectromechanical system (MEMS) technology in a clean room and characterized by impedance spectrums. An underwater testing system is established to conduct the experimental verification, whose results are in good accord with those of mathematical modeling. The sensor output voltage has fine linearity with the underwater acoustic pressure and achieves a flat frequency response. Moreover, the sensor has a sensitivity of −172.7 dB (Ref. 1 V/μPa) superior to the reported devices in the same categories. This work provides significant guidance for modeling radial field piezoelectric diaphragms and designing more efficient piezoelectric microsensors, which have a fine application prospect in underwater acoustic measurement.

Research on the artificial control method of the gas nuclei spectrum in the small-scale experimental pool under atmospheric pressure

Abstract With the improvement of the accuracy of experimental devices and measuring instruments, cavitation experiments such as cross-media vehicles and propellers have been carried out in small pools. However, the water quality in the laboratory and the engineering application waters differs, especially the concentration of the gas nuclei that cause cavitation, resulting in experimental results that differ from prototype experimental results, and the scale effect occurs. In order to reduce the influence of the scale effect, according to the conditions of cavitation, gas nuclei can be mixed with water before the experiment is formally implemented. Aeration behavior will affect the size and concentration of gas nuclei (gas nuclei spectrum) in water. In order to obtain better experimental results, it is necessary to clarify the variation of the gas nuclei spectrum in small-scale experimental pools before and after aeration, so as to master aeration technology. Through research, it is found that the artificial aeration method can effectively change the gas nuclei spectrum in water and increase the concentration of gas nuclei. By using the underwater acoustic measurement method, the change in the gas nuclei spectrum can be captured sensitively. The gas nuclei spectrum in water after aeration is in good agreement with the mathematical model of gas nuclei spectrum under non-artificial intervention, which shows that the distribution of gas nuclei in water under artificial aeration is similar to that under non-artificial intervention, which is conducive to the occurrence of cavitation. At the same time, it shows that the combination of experiment and numerical method can reduce the measuring state and the measurement cost and improve the measurement efficiency.

Feature extraction and classification of deep-sea mobile underwater acoustic channels

The reliable acoustic path (RAP) is one of the crucial channels for deep-sea sound propagation, which is affected weakly by the interface and has lower transmission loss, enabling long-distance communication. However, RAP-based deep-sea acoustic communication may face channel model mismatch issues. In order to analyze the dynamic characteristics of spatial-temporalvariability channels, deep-sea mobile underwater acoustic channel measurement experiments were conducted. This work proposes a deep learning method based on multi-dimensional properties to classify deep-sea channels. Specifically, the sound ray convergence zone leads to a complex multipath structure and severe delay spread in the RAP channel. The fuzzy c-means (FCM) algorithm is used for multipath clustering to extract accurate channel features, and then the Markov chain (MC) is introduced to track the evolution characteristics of multipath clusters. Finally, the coupling features of channel time-variant impulse response (TVIR) and multi-dimensionalstatistical properties are used as the input of convolutional neural networks (CNNs) to obtain the quantitative evaluation index as the channel classification to build a channel feature dataset for underwater mobile platforms. This dataset can effectively assist in identifying deep-sea mobile channels and promote the development of adaptive underwater acoustic communication systems on mobile platforms.

Shift-variant deconvolution beamforming using Implicit Neural Representation for near-field acoustic image measurement

The conventional beamforming (CBF) output can be expressed as a convolution of the source distribution and the array dependent point spread function (PSF), which is defined as the response of the beamformer to a point source. The resolution and accuracy of sound source localization can be improved by deconvolution of CBF. The shift-invariant PSF assumption is only a good approximation when the source region is small compared to the distance between the array and the source. However, the PSF of the near-field underwater acoustic map measurement is shift-variant, whose mismatch with the beam could lead to performance degradation. In this paper, we proposed an optimized deconvolution method by using the neural network called implicit neural representation (INR) to solve the beam mismatch problem, due to its strong performance in learning and reconstructing spatial scenes. Rather than recompute the PSF for each pixel in the scene, INR predicts the complex-valued weight matrix in two-dimensional space that encapsulates both the spatially varying properties of the PSF and the scatter distribution of the scene. Numerical simulations and experimental results verify the effectiveness of our method. And this work can be broadly applied to arrays with shift-variant PSFs.

Underwater Acoustic Intensity Analysis using Noise Assisted-MEMD with Varying Distances

With current developments, underwater communication using acoustic signals is widely used. Many things need to be prepared to support a reliable underwater communication system, such as taking measurements in a test tank to find out the correct measurement configuration. Underwater acoustic intensity measurements, which are detailed in this paper, are performed in the test tank using distance variation schemes. Measurements were made at various distances of 4, 10, 20, and 50 meters from the signal source. The hydrophone that was used has a sensitivity of -180 dB re 1V/µPa. The hydrophone was placed at a depth of 2 meters below the surface of the water in the test tank, which divided the test tank depth in half to ensure that reflections from the bottom and the surface were kept to a minimum. However, the problem is that there are noisy signals at different frequencies. This paper proposes a method using Noise Assisted - Multivariate Empirical Mode Decomposition (NA-MEMD) to decompose the signal and then calculate the sound intensity. The result shows that an increase in the distance between the transmitter and receiver, also causes a change in the intensity with an average change of 0.467 dB/meter. It is concluded that the NA-MEMD approach was shown to be successful in decomposing the intended signal from the noise to equalize the quality of the signal received at different distances, and the correlation between intensity value and change in distance is resilient, with a correlation value of 0.98, indicating a very strong correlation.

Method and Experiment Study of the Array Shape Calibration for Underwater Vertical Line Arrays

Vertical line arrays have been widely used in underwater target location and noise measurement, and the attitude and shape of the vertical array have a significant influence on detection accuracy. The paper presents an array shape calibration method for underwater vertical acoustic array-based measurement systems. Firstly, a standard acoustic source was used to transmit underwater acoustic signals at a certain distance from the acoustic array, and the target location based on the received data of the acoustic array was estimated concerning distance and depth to obtain the two-dimensional ambiguity function of the depth and distance of the array. Then, the ambiguity function was used to calculate the center depth and the inclination angle of the vertical acoustic array and to further obtain the shape and location information of the acoustic array. Finally, a lake experiment study was carried out. The results showed that the calibrated array shape was in good agreement with the actual location, and the sound source location estimated by using the calibrated array shape was consistent with the actual sound source location, thereby effectively reducing the impact on the measurement accuracy due to the inclination of the measurement system under the influence of water current.

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

Using passive acoustic methods for biodiversity conservation and effective ecosystem monitoring is hindered by laborious, human-mediated processes of accurately identifying biologic and anthropogenic sounds within large datasets. Soundscape ecology provides a potential means of addressing this need through the use of automated acoustic-based biodiversity indices, which show promise in representing biodiversity in terrestrial environments. However, the direct relationship between specific underwater sounds and acoustic index measurements are largely unexplored. Using passive acoustic data collected from three broadband hydrophones within the Ocean Observatories Initiative’s cabled arrays in the Pacific northwest, we identified periods of vocalizing marine mammals and sources of anthropogenic noise. Automated calculations of seven acoustic indices were compared across biologic and anthropogenic sound type and call parameters. Although several index measurements did not vary significantly, the Acoustic Complexity Index (ACI) measurements increased in response to echolocation clicks from sperm whales (Physeter macrocephalus) and burst pulses originating from unidentified delphinid species. Measurements of the Bioacoustic Index (BI) decreased dramatically in response to sperm whale echolocation clicks, a more obvious trend when loud clicks were parsed from moderate and quiet clicks. Correlations coefficient and confidence interval values between ACI and BI measurements and call characteristics from sperm whales indicate a moderate to strong relationship, which was not found in correlations with delphinid calls. A generalized linear mixed-effect model indicated multiple species and sound types contribute significantly to the variation of several index measurements. Noise generated by passing ships consistently resulted in decreased values for the Normalized Difference Soundscape Index (NDSI) and Total Entropy (H) as compared to quiet periods and periods with vocalizing marine mammals. These findings provide information on the relationship between several acoustic indices and specific underwater sounds produced by marine mammals and anthropogenic sources. This ground-truthing endeavor expands the understanding of acoustic indices and their potential use as a tool for conservation and ecosystem health management purposes.

The underwater sound levels of Lithuanian marine harbour

Aquatic animals rely on sound to communicate, navigate, prey, or avoid predation in turbid waters. The acoustic environment of their habitats plays an important role in their life, i.e. the fishes understand the environment using sound. Documented studies provide data indicating that marine habitats can be altered by anthropogenic noise, due to which marine life can be affected. The nearshore and the areas of harbours are usually predominated by the high sound pressure levels of anthropogenic origin resulting from frequent passages of pleasure vessels and other kind of ships nearby. These high levels no doubt can cause the risk of negative effects on marine life inhabited or migrating through nearshore and harbour areas. With the aim to assess the underwater sound levels at Klaipėda harbour area, underwater acoustic measurements were implemented. The obtained results indicate that the Klaipeda harbour is affected by the anthropogenic underwater noise and long-term noise monitoring may be useful to assess the trends of prevailing underwater noise in this area. In this paper, the results of the continuous underwater sound level measurements along with the analysis of the influence of anthropogenic sources and environmental factors on prevailing soundscape are presented; the risks of negative effects of elevated underwater noise levels on fish species and possible underwater noise measures are shortly discussed.

Automated acoustic arrival matching using a convolutional neural network approach informed by statistics of acoustic scattering from internal waves

A machine learning model was developed to automatically align underwater acoustic measurements taken at various depths and ranges from a transmitting source in the Philippine Sea to a reference model of long range acoustic arrival structure, simultaneously determining source-receiver range and travel-time offsets associated with multipath arrivals. Ocean sound-speed variability complicates the task as the measured arrivals may exhibit scattering not present in range-independent predictions. Monte Carlo style broadband parabolic equation simulations through random internal wave fields consistent with the Garrett-Munk internal wave energy spectrum were used to generate a large data set of simulated acoustic receptions including scattered multipath arrivals with known source-receiver ranges and imposed travel time offsets. These simulated receptions were used to train and evaluate the machine learning model for arrival pattern matching to the reference model. The inclusion of various data dimensions, such as peak amplitude and width, and contextual information, such as range and depth, were also explored as input to the model. Ranging results for the machine learning model were compared to a programmatic solution engineered for the same task.

An Acoustic Sea Glider for Deep-Sea Noise Profiling Using an Acoustic Vector Sensor

Abstract An acoustic sea glider has been developed for ambient sea noise measurement and target detection through the deployment of an acoustic vector sensor (AVS). The glider was designed with three cabins connected in sequence and it can dive to depths exceeding 1200m. The AVS fixed on the glider measure acoustic pressure and particle velocities related to undersea noise, and the inner attitude sensors can effectively eliminate the estimation deviation of the direction of arrival. The inherent self-noises of the acoustic sea glider and AVS are presented respectively in respect to the Knudsen spectra of sea noise. Sea trial results indicate that the AVS could work well for undersea noise measurement when the glider is smooth sliding, and the target azimuth estimated by AVS after correction is remarkably consistent with the values measured by the GPS, and direction-finding errors are less than 10 degrees. The research in this paper shows that the acoustic sea glider is able to undertake tasks such as a wide range of underwater acoustic measurement and detection.

Fabrication and calibration of nanostructured vanadium-doped ZnO-based micromachined sensor with superior sensitive for underwater acoustic measurement

A high-performance micromachined piezoelectric sensor based nanostructured vanadium-doped zinc oxide (ZnO) film with air-backing has been developed and characterized for underwater acoustic application. The sensing cell with a low foot-print of 2.0 mm × 2.0 mm is fabricated by Micro electro mechanical systems (MEMS) technology using a ZnO-on-silicon-on-insulator process platform. An optimal ratio of piezoelectric coefficient to the relative permittivity is obtained about 6.3 in the Zn0.98V0.02O sensing cell, improving by an order of magnitude compared with other notable piezoelectric films, plays a mainly dominant role in the enhanced piezoelectric response. Calibrations in the standard underwater instrument have demonstrated that the presented sensor could achieve an acoustic pressure sensitivity of −165 ± 2 dB (1 V μPa−1) over a bandwidth 10 Hz–10 kHz, outperforming the same kind of reported devices. The maximum non-linearity is no more than 0.3%, the sensitivity variation is no more than ±0.7 dB in the temperature range from 10 °C to 50 °C, indicating a better stability and higher reliability. The proposed sensor with a superior acoustic sensitivity gives a great application potential in underwater acoustic measurements.

Comparison of the performance characteristics of the tonpilz transducers fabricated from 0.60PMN-0.40PT & PZT piezoceramics

In this study, tonpilz transducers based on 0.60Pb(Mg1/3Nb2/3)O3-0.40PbTiO3 (60PMN-PT) and commercially available lead zirconate titanate (PZT) compositions (PZT 4, PZT 5H, PZT 8 and PZT 5A) were designed, fabricated, characterized and compared for their underwater performance. Each stack is composed of two rings of PZT or PMN-PT ceramics. Transducers were designed and analyzed using the commercial ATILA finite elements analysis (FEA) code. Commercially available powders were used for PZT, whereas 60PMN-PT powders with pure perovskite phase were synthesized using solid-state reaction route. Ceramic rings have been produced using dry pressing. Dielectric, piezoelectric and electromechanical properties of the rings were calculated using the resonance method. Vibration modes of the rings and transducers constructed from various types of piezoceramics were analyzed using FEA. The main resonance frequency of the tonpilz transducer belonging to the longitudinal piston mode was measured in the mid-frequency range between 30 and 35 kHz. Underwater acoustic measurements were conducted on polymer-coated transducers, and their performances were compared for possible underwater acoustic applications. Transducers fabricated from 60PMN-PT were found to have comparable underwater performance with that of PZT 4, where the Transmitting Voltage Response (TVR) reached 135 − 136 dB re 1 µPa/V @1 m range with a −3dB bandwidth of 4 kHz. These results indicated the viability of using 60PMN-PT ceramics in active device applications in an array form.

Automated matching of long range underwater acoustic arrivals to predictions using a minimum variance Approach

An automated method was developed to align underwater acoustic measurements taken at various depths and ranges to a reference model of acoustic arrival structure. Data used to demonstrate the method were collected by four autonomous underwater vehicles deployed in the Philippine Sea as part of an ocean acoustic tomography experiment. The arrivals were measured in the upper 1000 m of the ocean at ranges spanning several hundred kilometers from 5 moored acoustic tomography sources. The primary objective is to accomplish automatic source-receiver ranging by aligning measurements of long range acoustic arrivals to a single reference model. Acoustic arrival time structure for pulse compressed signals at long ranges is relatively stable, yet real ocean variability presents challenges in acoustic arrival matching. The presence of internal waves scatters the acoustic arrival structure and can introduce spurious arrivals in the measured data. This method takes advantage of simple projections of the measured structure onto the model space with constraints informed by scattering statistics consistent with the Garrett Munk internal wave energy spectrum. Compared to manual matching of the measured arrivals to eigenray models, more than 90% of the automatically obtained range estimates were within 150 m of the manually obtained range estimates.

Underwater sound generated by motor vehicle traffic in an underwater tunnel

Underwater acoustic and environmental measurements were made adjacent to the Monitor-Merrimac Memorial Bridge-Tunnel in the James River in Virginia during a field experiment in April 2019. The observed sound field exhibited short time-scale and tidal time-scale variability due to passing marine vessels and tidally driven currents in the estuary; most interestingly, the sound field exhibited variability on a diurnal time scale, closely correlated to the temporal distribution of vehicular traffic in the underwater tunnel. During morning and evening rush-hour traffic periods, the amplitude of the traffic-induced underwater signal exceeded 10 dB at 40 Hz. Additional physics-based modeling and direct observation are required to verify the hypothesis that the signal is associated with the traffic-induced vibration in the tunnel roadbed.

RSS-based underwater acoustic distance measurement with multiple frequencies

Among various underwater ranging techniques, received signal strength (RSS)-based ranging method enjoys great popularity because of its accessibility and low cost. However, this effective method encounters great performance challenges due to multipath phenomenon.In this paper, to accurately map RSS values to distance in the multipath environment, ray tracing method based on image sources is introduced into the Urick propagation model. In this way, we can better obtain the relationship between RSS and parameters containing distance in the new transmission model. However, since these parameters cannot be derived with only one RSS measurement, we utilize multiple RSS measurements at different frequencies to calculate them. Moreover, since the mapping problem between RSS and distance is ill-conditioned, we construct additional inequalities based on prior information of the scene, and then present an algorithm named interior-point, to solve the problem.We analyze the proposed scheme to derive the lower bound, and numerical simulation shows ranging error is minor and almost falls on the top of CRLB. The results in next simulations and experiment show the localization performance is close to the state-of-art method based on compressed sensing and ranging accuracy improves up to 2 times when compared to the conventional method.

Observations on relations between marine aerosol fluxes and surface-generated noise in the southern Baltic Sea

Summary This study presents the preliminary results of combining underwater acoustic ambient noise measurements with those of in-situ sea spray fluxes (SSF). Hydroacoustic measurements (in the frequency range 80 Hz –12.5 kHz) were made using an underwater noise recording system developed at the Institute of Oceanology of the Polish Academy of Sciences which was then deployed in the southern Baltic Sea. The simultaneous measurements of coarse sea spray fluxes (with particle diameters ranging from 0.5 to 47 µm) were made on board the r/v Oceania using the gradient method. Observations were conducted for the duration of the passage of an atmospheric front that lasted 2.5 days (60 hours of measurements). There were significant differences in the sound pressure level (SPL) and aerosol fluxes observed between the first part of measurements (developing wave state) and the second part (developed waves). Wave parameters, such as peak period, significant wave height, wave age, and mean wave slope acquired from the WAM (WAve Model), were used to investigate the impact of wave field properties on noise and aerosol flux measurements. We observed different behaviours in the power spectrum density (PSD) levels of noise for these parameters depending on the wave state development.