Noise In Shallow Water Research Articles

Off-grid hydroacoustic signal orientation estimation based on interpolation and subspace fitting in coprime arrays.

This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. The proposed method incorporates interpolation of the coprime array and signal subspace fitting. It addresses the limitations of the hydrophone coprime array in utilizing all array elements' information and mitigates the interference of ocean noise in shallow waters, which impairs the accuracy and resolution of target direction estimation. Firstly, the hydroacoustic signals are received using a coprime array, then the missing information is filled by interpolating the virtual array elements in the virtual domain, and by optimizing the design of the atomic norm and reconstructing the covariance matrix, the direction-of-arrival (DOA) estimation is performed using all the information of the received signal. Then, the received signal is reconstructed in conjunction with the reconstructed covariance signal subspace, which effectively reduces the impact of background noise. Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.

Observation and Modelling on the Shipping Noise in Shallow Waters with Complex Islands and Reefs of the East China Sea

The impact of the noise radiated from merchant ships on marine life has become an active area of research. In this paper, a methodology integrating observation at a single location and modelling the whole noise field in shallow waters is presented. Specifically, underwater radiated noise data of opportunistic merchant ships in the waters of Zhoushan Archipelago were collected at least one day in each month from January 2015 to November 2016. The noise data were analyzed and a modified empirical spectral source level (SSL) model of merchant ships was proposed inspired by the RANDI-3 model (Research Ambient Noise Directionality) methodology. Then combining the modified model with the realistic geoacoustic parameters and AIS data of observed merchant ships, the noise mappings in this area were performed with N×2D of Normal Mode calculations, in which the SSL of each ship was estimated using the modified model. The sound propagation at different receiving positions is different due to the shielding effect of islands and bottom topography. The methodology proposed in this paper may provide a reference for modelling shipping noise in shallow waters with islands and reefs.

Estimation of seabed properties from ocean ambient noise in shallow water: A review

Ocean ambient noise is the sound persisting in the ocean, which includes contributions from natural and anthropogenic sources, such as rain, wind, shipping, and marine mammals. Multiple interactions of the sound with the surface and bottom in shallow water affect the spatial characteristics of ambient noise. Thus, the spatial noise properties, coherence, and directionality of ambient noise depend on the characteristics of the shallow water environment, such as depth, sound speed profile, and seabed sediment properties. Acoustic properties of seafloor sediments can be extracted from ambient noise based on these noise properties using various types of noise data and geo-acoustic inversion methods. This paper presents a review of literature concerning investigations into available methods, the implementations of these methods, and their verification and validation. The efficacy and the applicability of these inversion methods for a wide range of ocean noise data are also examined in this review.

Propagation of ship noise in shallow water over a high shear-speed seabed

Assessing the acoustic impact of shipping close to the coast and within ports and harbours requires an understanding of the propagation of underwater sound in these environments. In the Australian context, this often means propagation over seabeds with shear speeds approaching the in-water sound speed, a situation that results in very different propagation conditions to the low shear speed sediments more commonly encountered in other parts of the world. Acoustic propagation modelling approaches were explored using a dataset of continuous underwater recordings featuring a mix of shipping, industrial, and recreational activities, acquired from 23 Jul to 16 Sep 2022 in Cockburn Sound, off the west coast of Australia. Cockburn Sound is a sheltered marine embayment with a relatively uniform water depth of 17–20 m in the 5 km × 11 km central portion of the basin, with a thin, variable thickness (0.5 m–5 m) layer of silty sediments overlying a calcarenite basement. The results of modelling the calcarenite basement as an equivalent fluid were compared to those obtained by modelling it as an elastic solid, and with measurements. Subsequent implications of the choice of geoacoustic model will be discussed

Measuring vessel underwater radiated noise in shallow water.

Performing reproducible vessel source level (SL) measurements is complicated by seabed reflections in shallow water. In deep water, with a hydrophone far from the seabed, it is straightforward to estimate propagation loss (PL) and convert sound pressure level (SPL) into SL using the method codified in the international standard ISO 17208-2 [International Organization for Standardization (ISO), Geneva, Switzerland (2019)]. Estimating PL is more difficult in shallow water because of the way that sound reflects from the seabed such that multiple propagation paths contribute to SPL. Obtaining reproducible SL measurements in shallow water requires straightforward and robust methods to estimate PL. From May to July 2021, a field experiment evaluated different methods of measuring vessel SL in shallow water. The same vessels were measured many times in water depths of 30, 70, and 180 m. In total, 12 079 SL measurements were obtained from 1880 vessel transits and 16 hydrophones, distributed across 3 moored vertical line arrays and 2 moored horizontal line arrays. The experiment confirmed that it is possible to obtain reproducible vessel SL estimates in shallow water comparable to within ±2.5 dB of ISO-compliant measurements in deep water and repeatable to within ±1.5 dB.

A Viterbi Decoder under Class A Modeled Noise in Shallow Water

A traditional Viterbi decoder is primarily optimized for additive white Gaussian noise (AWGN). With the AWGN channel, it offers good decoding performance. However, the underwater acoustic communication (UAC) channel is extremely complicated. In addition to white noise, there are a variety of artificial and natural impulse noise that occur suddenly. The traditional Viterbi decoder cannot obtain the optimum performance under this case. In order to solve this problem, this paper introduces a novel Viterbi decoder with the impulsive noise, which is considered to be subjected to Middleton Class A distribution in shallow ocean. Since Middleton Class A noise is very complicated, a simplified model is first introduced. Then, the error analysis of simplified model under various parameters is discussed in detail. The analysis shows that the simplified one just leads to slight error. Hereafter, a novel Veterbi decoder using the simplified model is discussed. Compared to a traditional decoder, a preprocessing is just required. The performance of soft decision-based decoder in the Middleton Class A noise channel (MAIN) and AWGN are further compared. Based on our simulations, the new decoder can significantly improve the performance in comparison with conventional one, which further validates our presented method.

Direction of arrival estimation under Class A modelled noise in shallow water using variational Bayesian inference method

The shallow water noise shows obvious impulsive property, which greatly degrades the direction of arrival (DOA) performance due to the conventional design concept based on the Gaussian assumption. In this paper, DOA estimator in presence of impulsive noise utilising variational Bayesian inference is proposed. The Middleton's Class A noise model is considered as a typical underwater noise model to analyse the performance of DOA estimation. The DOA estimation problem is modelled as the sparse signal recovery problem, and the hierarchical Bayesian learning framework is formulated by considering the common sparsity of signal and the element-wise sparsity of the impulsive noise. The variational Bayesian inference realises the posterior estimation of signal and impulsive noise components. To mitigate the basis mismatches, the root sparse Bayesian learning method is applied to refine the steering vectors. Simulations verify the advantages of the proposed DOA method in terms of spatial resolution, root mean square error, accuracy, and robustness compared with the state-of-the-art benchmarks in the presence of Middleton's Class A noise.

Modal dispersion curve extraction from shipping noise at two synchronized vertical arrays

The results of modal dispersion analysis, using low-frequency (20 to 250 Hz) shipping noise in shallow water with a soft bottom is presented. Experiments were carried out in the Sea of Galilee (Lake Kinneret, Israel) having a maximum depth of ∼40 m and a gassy upper sedimentary layer. A receiving system combined two synchronized, 10-hydrophone vertical line arrays (VLAs) located at the center of the lake with distance Dr = 40 m between them. The noise source, R/V “Hermona,” was moving along the straight line joining VLAs, up to 1 km from VLAs. A method of obtaining modal dispersion curves from shipping noise is proposed. For each frequency ω and variable horizontal wavenumber q = ω/cph the noise is spatially filtered at each VLA using calculated solution of the wave equation with the measured sound speed profile in water and the pressure-release condition imposed at the water surface. Then, the ratio of complex modal amplitudes at VLAs is calculated and multiplied by a factor of . The real part of the resulting 2-D structure exhibits the modal dispersion curves, which are used for acoustic characterization of the seabed. [Work supported by ISF, grant 946/20, and RFBR, grant 20-05-00119.]

Head-wave correlations in layered seabed: Theory and modeling.

This paper derives travel times and arrival angles of head-wave correlations from ocean ambient noise in shallow water over a layered seabed. The upcoming and surface reflected head-wave noise signal received at two receivers from the same interface are correlated, and their travel time differences give the travel times of the head-wave correlations. The arrival angle of head-wave correlations from an interface depends on sound speeds in the layers above and just below. The predictions of head-wave correlations from a seabed with two layers and the corresponding inversion results are verified with simulations.

Sparse Bayesian Learning Based Direction-of-Arrival Estimation under Spatially Colored Noise Using Acoustic Hydrophone Arrays

Direction-of-arrival (DOA) estimation in a spatially isotropic white noise background has been widely researched for decades. However, in practice, such as underwater acoustic ambient noise in shallow water, the ambient noise can be spatially colored, which may severely degrade the performance of DOA estimation. To solve this problem, this paper proposes a DOA estimation method based on sparse Bayesian learning with the modified noise model using acoustic vector hydrophone arrays. Firstly, an applicable linear noise model is established by using the prolate spheroidal wave functions (PSWFs) to characterize spatially colored noise and exploiting the excellent performance of the PSWFs in extrapolating band-limited signals to the space domain. Then, using the proposed noise model, an iterative method for sparse spectrum reconstruction is developed under a sparse Bayesian learning (SBL) framework to fit the actual noise field received by the acoustic vector hydrophone array. Finally, a DOA estimation algorithm under the modified noise model is also presented, which has a superior performance under spatially colored noise. Numerical results validate the effectiveness of the proposed method.

Parameter estimation of underwater impulsive noise with the Class B model

The statistical characteristic of ocean ambient noise plays an important role in developing underwater signal processors. Considering that the noise in shallow water shows the impulsive nature, non-Gaussian noise models are usually applied to model the ocean ambient noise. In this study, the ocean ambient noise is modelled by using the Middleton Class B model, which can be decomposed into Gaussian and non-Gaussian models. Then, the parameters of Class B model are estimated based on the least-square estimation method, which can be deduced by using the characteristic function of the Middleton Class B model. The processing results of simulated data and real data indicate that the presented method well estimates the parameters of Class B modelled noise. Besides, it further shows that the Middleton Class B model is suitable for modelling the impulsive noise in shallow water.

Effects of islands and downslope seafloors on underwater noise in the northern South China Sea during a typhoon

The correlation of ambient noise with wind speed, and the depth dependence of ambient noise are both investigated, where the ocean noise data were recorded by a vertical line array in the northern South China Sea. It is shown that the correlation coefficients increase with increasing hydrophone depth during typhoon periods when the frequency ⩾ 250 Hz, which opposes the generally accepted knowledge that the correlation coefficients of noise level and wind speed decrease with increasing depth during non-typhoon periods. Particularly at frequencies of 250 Hz, 315 Hz and 400 Hz, the correlation coefficients increase by more than 0.05 at depths ranging from 155 m to 875 m. At the three frequencies, the average noise levels also increase with increasing depth during typhoon periods. It is suggested that these differences are attributed to the wind-generated noise in shallow waters and the effect of “downslope enhancement” to sound propagation. During typhoon periods, the surf breaking and surf beat upon the shores and reefs are strengthened, and the source levels are increased. The wind-generated noise in shallow waters interacts with the downslope sea floor, with the noise-depth distribution changed by a “downslope enhancement” effect promoting noise propagation.

Acoustic behavior of snapping shrimp in east china sea

Ambient noise in shallow water is typically more complicated than that in deep sea. The snapping shrimp, which is a major source of ambient noise in shallow water, produces impulsive-shape noise. During the period of 14–28 May 2015, the Shallow-water Acoustic Variability Experiment (SAVEX15) was performed in the East China Sea (ECS) at a shallow water off the southwest of Jeju Island, Korea. In the study area, snapping shrimp noise was recorded continuously with dominant frequencies higher than 3 kHz. Envelope correlation method combined with the threshold detection was used to extract the snapping events from the received ambient noise data. Although many previous research studies have reported that the diurnal variation of snapping shrimp noise is mainly due to water temperature variation controlled by light availability, the observed snap rates in our experimental site showed unusual sinusoidal pattern and seemed to be positively correlated with the phase of the tidal current. [Work supported by the Development of Civil Military Technology Program (No. 18-SN-RB-01) from the Institute of Civil Military Technology Cooperation (ICMTC) of the Republic of Korea.]

Michael J. Buckingham: Leading the way in ocean ambient noise processing and modeling

Nearly 40 years ago, Michael Buckingham published a theoretical model for ocean ambient noise in shallow water. His pioneering work of the late 1970s and early 1980s advanced not only the methods for understanding the ambient noise field but also the impact on array signal processing. In the late 1980s, Buckingham made a pivotal shift in thinking about ambient noise. He considered ambient noise not as a nuisance factor but as a usable signal. In the late 1980s Buckingham and Jones had the novel idea to take measured ambient noise from a vertical line array and develop an inversion method to determine the seabed critical angle. A few years later, Buckingham invented a technique known as ambient noise imaging (ANI), or acoustic daylight, which is analogous to conventional photography with daylight as the source of illumination. Buckingham continues to lead the way, and the true significance of his work must include the inspiration his research gives to numerous other scientists, especially those investigating methods to exploit ambient noise as a usable signal. In this presentation, a review of Buckingham’s contributions to understanding ambient noise will be described, particularly as they relate to recent methods for ambient noise processing and modeling.

Parameter Estimation for Class A Modeled Ocean Ambient Noise

A Gaussian distribution is used by all traditional underwater acoustic signal processors, thus neglecting the impulsive property of ocean ambient noise in shallow waters. Undoubtedly, signal processors designed with a Gaussian model are sub-optimal in the presence of non-Gaussian noise. To solve this problem, firstly a quantile-quantile (Q-Q) plot of real data was analyzed, which further showed the necessity of investigating a non-Gaussian noise model. A Middleton Class A noise model considering impulsive noise was used to model non-Gaussian noise in shallow waters. After that, parameter estimation for the Class A model was carried out with the characteristic function. Lastly, the effectiveness of the method proposed in this paper was verified by using simulated data and real data.

Eigenvalues of the sample covariance matrix for a vertical array in shallow water

The eigenvalue spectrum of the sample covariance matrix (SCM) contains valuable information about the environment and the source and noise generation. Random Matrix Theory (RMT) combined with physical models is used to explain the eigenvalue distribution. For conventional three-dimensional and two-dimensional free space isotropic noise models, there is a jump in the eigenvalue spectrum of SCM which only depends on array properties (element spacing to wavelength ratio). This paper investigates the eigenvalue distribution of SCM for a vertical array in shallow water noise environment using Harrison’s noise model [Harrison, J. Acoust. Soc. Am. 99, 2055-2066 (1996)]. Results show that when bottom is considered, the jump location depends on both array and bottom properties. RMT is applied to study the eigenvalue spectrum estimation with different sound speed and attenuation in the bottom. Shallow water vertical array data are analyzed and it is demonstrated that the eigenvalues of the SCM compare well with theory.

Tomographic inversion of measured cross-correlation functions of ocean noise in shallow water using ray theory

Based on experimental data obtained in 2012 in the Florida Strait, we study the feasibility of employing ray tomography to retrieve sound speed and flow velocity profiles from measured noise cross-correlation functions. We describe the results of numerical experiments that characterize the inversion errors resulting from peculiarities of the ray structure in shallow water, difficulties in unambiguous identification of ray arrivals, and a decrease in accuracy of ray theory at low frequencies. We show that under conditions of low-mode sound propagation, the use of the classical ray tomography scheme can yield only a rough estimate of the sound speed profile, but it allows approximate reconstruction of the current velocity profile. Application of passive ray tomography to the experimental data yields the current velocity profile in the Straits of Florida, which agrees with independent measurements within the inversion error limit.

Ambient Noise Analysis and Modeling in Shallow water of Arabian Sea

work presents a shallow water ambient noise analysis and modeling effort in the Arabian Sea. Real ambient noise recording at very shallow depths has been analyzed for two environmentally unique periods when the sound velocity profile and the wind conditions present distinct characteristics. Ambient noise data were collected for January and March in the shallow water of Arabian Sea between the wind speed 0.0 m/s to 4.11 m/s. The relative spectral energy distribution of sea noise is presented for a number of wind speeds. Linear relationship between the sea noise spectrum levels and the wind speed were found for the entire frequency range, but the slope were frequency dependent. The results of empirical fitting based on the analysis were used for noise level prediction and the model predictions were compared with the measured noise level. Such study post extensive validation has the potential to develop predictive models for ambient noise estimation based on recorded data. dependent coefficient. The ambient noise was also shown to be site specific in shallow water where speed of the sound and the bottom properties vary substantially with the location. Gayer & Wille (1984) in their work made measurements in North Sea and Baltic Sea and reported that the influence of propagation loss on the wind dependent shallow water noise appears to be marginal even at extremely different area. It was observed that the contradicting behavior of the summer and winter noise levels was due to wind stress at sea surface. Similar work by Ingenito (1989) on site dependence of wind- dominated ambient noise in shallow water reported lower noise level of around 2 dB in the silt bottom at wind speed of 7 m/s when compared to sand bottom at wind speed 3-5 m/s and variability of 10 dB in the average noise spectrum level was observed in the essential fraction of the entire range of the spectrum. The large spread of wind generated noise levels measured for the same wind speed and wave height in the absence of other noise sources is essentially attributed to the site dependence and the primary site dependent factor that influence the noise level being acoustic propagation which in turn are dependent on the season, ocean depth and the bottom composition . Piggott (1964), has reported a logarithm relation for the ambient noise and the wind speed based on his study at two depths in very shallow water (36 m and 51 m), where the non wind dependent factors were reported to be not significant and the contribution of the wind dominated source was observe to be dominant at nearly all wind speeds and all frequencies. The relation has been extensively validated by numerous researchers and adapted for varying sites. The relation is presented below for reference:

A few Canadian contributions to underwater acoustics

An historical perspective on four Canadian initiatives in underwater acoustics will be presented: Towed Variable Depth Sonar (TVDS); the Chapman-Harris model for reverberation; seabed-interaction in shallow water; and Arctic acoustics. The poor performance of hull-mounted sonars in Canadian waters during WWII prompted TVDS development in 1947. The resulting prototype (CAST/1X) was tested against a UK developmental system in 1958. Subsequently, the UK purchased the Canadian system and the US re-packaged their sonars according to the Canadian design. An understanding of the effects of back-scattering from the sea surface and bottom was required to model sonar system performance. Experiments began circa 1960 leading to a new model for sea surface back-scattering, and revealing the ocean volume as an additional factor. The conditions governing propagation and noise in shallow waters remained mysterious in the 1970s, until the significant role of the seabed emerged through theoretical developments (e.g., loss due to shear waves) and experiments conducted over a variety of seabed types. Political, sovereignty and energy issues prompted Canada to investigate under-ice acoustics in the Arctic beginning circa 1958. The efforts ultimately resulted in the ability to undertake under-ice acoustic and geophysical surveys using long endurance Autonomous Underwater Vehicles (AUVs).

Geoacoustic inversion of ship radiated noise in shallow water using data from a single hydrophone.

The Centre for Maritime Research and Experimentation conducted a geoacoustic inverse experiment in the Mediterranean Sea in the summer of 2012. Among the objectives was to employ an autonomous underwater vehicle to collect acoustic data to invert for properties of the seafloor. Inversion results for the compression wave speed in the bottom and the source spectrum of the R/V Alliance during a close approach to the bottom moored vehicle are presented. The estimated wave speed was 1529 m/s (σ=10). The source spectrum of the Alliance was estimated across more than six octaves of frequency.