Towed Array Research Articles

The hydrodynamic noise suppression of the towed array by the combination of the flow and sustained release

Abstract This paper proposes a jet flow release method based on fish mucus to reduce the flow noise of the towed array. This method aims to alleviate the adverse effects of turbulent fluctuating pressure on the self-noise of a towed array at high speeds and address the problem of target signal masking caused by flow noise. A circular jet nozzle is installed at the front end of the towed array to spray mucus backward, reducing the turbulent fluctuating pressure on the surface of the towed array and improving the signal-to-noise ratio. Large eddy simulation using Fluent and finite element calculation of the acoustic field using Actran are employed to obtain flow and acoustic field results, respectively. The research findings demonstrate that after spraying mucus through the jet nozzle, the model’s viscous drag is reduced, and the excitation on the surface is significantly decreased, leading to a noticeable reduction in the self-noise sound pressure level in the frequency range of 150–2000 Hz.

Use of whistles for acoustic classification of delphinids (odontoceti: Delphinidae) in the Western South Atlantic Ocean.

This study focuses on the acoustic classification of delphinid species at the southern continental slope of Brazil. Recordings were collected between 2013 and 2015 using towed arrays and were processed using a classifier to identify the species in the recordings. Using Raven Pro 1.6 software (Cornell Laboratory of Ornithology, Ithaca, NY), we analyzed whistles for species identification. The random forest algorithm in R facilitates classification analysis based on acoustic parameters, including low, high, delta, center, beginning, and ending frequencies, and duration. Evaluation metrics, such as correct and incorrect classification percentages, global accuracy, balanced accuracy, and p-values, were employed. Receiver operating characteristic curves and area-under-the-curve (AUC) values demonstrated well-fitting models (AUC ≥ 0.7) for species definition. Duration and delta frequency emerged as crucial parameters for classification, as indicated by the decrease in mean accuracy. Multivariate dispersion plots visualized the proximity between acoustic and visual match data and exclusively acoustic encounter (EAE) data. The EAE results classified as Delphinus delphis (n = 6), Stenella frontalis (n = 3), and Stenella longirostris (n = 2) provide valuable insights into the presence of these species between approximately 23° and 34° S in Brazil. This study demonstrates the effectiveness of acousting classification in discriminating delphinids through whistle parameters.

Imaging Seafloor Features Using Multipath Arrival Structures

In this paper, we propose an imaging method for seafloor features based on multipath arrival structures. The bistatic sonar system employed consists of a vertical transmitting array and a horizontal towed array. The conventional back projection (BP) method, which considers the direct path from the source to the seafloor scatterer and then to the receiver, is used in this system. However, discrepancies between the calculated delay values and the actual propagation delay result in projection deviations and offsets in the seafloor features within sound intensity images. To address this issue, we analyze the multipath structures from the source to the scatterer and then to the receiver based on ray theory. The delay at each grid is calculated using different multipaths, considering the distances from the seafloor grids to the source and the receiver. In the direct zone, the delay is determined using the direct ray and the surface reflection ray, while in the bottom bounce area, the delay is calculated using the bottom–surface reflection ray and the surface–bottom–surface reflection ray. Numerical simulations and experimental results demonstrate that the proposed method rectifies the delay calculation issues inherent in the conventional method. This adjustment enhances the accuracy of the projection, thereby improving the imaging quality of seafloor features.

Fast joint estimation of direction of arrival and towed array shape based on marginal likelihood maximization

This paper addresses the joint estimation problem of directions of arrival of sources and towed array shape. Ocean currents and the maneuvering of the towing platform often cause the towed array to bend rather than stay in a straight line, so the array shape must be estimated to avoid performance degradation due to array mismatch. Existing joint estimation methods suffer from high computational complexity or the need for external sensors installed on the array. Therefore, this paper proposes a fast joint estimation algorithm that solely utilizes received acoustic data. The joint estimation is transformed into a sparse reconstruction optimization problem within the Bayesian estimation framework. Firstly, by decomposing the marginal likelihood function, a closed-form solution for the signal variance in the spatial domain is obtained. Then, the towed array shape is introduced as a hyperparameter into the marginal likelihood function and optimized using the quasi-Newton method. In this way, we accomplish joint estimation and reduce computational complexity. Multi-source simulation results show that the proposed method achieves high resolution and fast computational speed. The robustness and efficiency of the proposed joint estimation method are demonstrated by experimental results in the South China Sea.

Direction-Finding Study of a 1.7 mm Diameter Towed Hydrophone Array Based on UWFBG.

This paper investigates a 1.7 mm diameter ultra-weak fiber Bragg grating (UWFBG) hydrophone towed array cable for acoustic direction finding. The mechanism of the underwater acoustic waves received by this integrated-coating sensitizing optical cable is deduced, and it is shown that the amplitude of its response varies with the direction of the sound wave. An anechoic pool experiment is carried out to test the performance of such a hydrophone array. The test array is a selection of six sensing fibers, each of which is coiled into 9 cm diameter fiber ring suspended in the water to receive acoustic signals. An average sensitivity of -141.2 dB re rad/μPa at frequencies from 2.5 kHz to 6.3 kHz was achieved, validating the detection of the azimuth of underwater acoustic waves. The ultra-thin towing cable system, with free structure, high sensitivity, and underwater target-detection capability has demonstrated great potential for future unmanned underwater vehicle (UUV) applications.

Deblurring of Beamformed Images in the Ocean Acoustic Waveguide Using Deep Learning-Based Deconvolution

A horizontal towed linear coherent hydrophone array is often employed to estimate the spatial intensity distribution of incident plane waves scattered from the geological and biological features in an ocean acoustic waveguide using conventional beamforming. However, due to the physical limitations of the array aperture, the spatial resolution after conventional beamforming is often limited by the fat main lobe and the high sidelobes. Here, we propose a method originated from computer vision deblurring based on deep learning to enhance the spatial resolution of beamformed images. The effect of image blurring after conventional beamforming can be considered a convolution of beam pattern, which acts as a point spread function (PSF), and the original spatial intensity distributions of incident plane waves. A modified U-Net-like network is trained on a simulated dataset. The instantaneous acoustic complex amplitude is assumed following circular complex Gaussian random (CCGR) statistics. Both synthetic data and experimental data collected from the South China Sea Experiment in 2021 are used to illustrate the effectiveness of this approach, showing a maximum 700% reduction in a 3 dB width over conventional beamforming. A lower normalized mean square error (NMSE) is provided compared with other deconvolution-based algorithms, such as the Richardson–Lucy algorithm and the approximate likelihood model-based deconvolution algorithm. The method is applicable in various acoustic imaging applications that employ linear coherent hydrophone arrays with one-dimensional conventional beamforming, such as ocean acoustic waveguide remote sensing (OAWRS).

Distributed shape detection for an acoustic sensitive optical cable with DAS.

Acoustic sensitive optical cables (ASOCs) and their shape detection are vital in underwater acoustic monitoring, and a distributed ASOC shape detection method is demonstrated with distributed acoustic sensing (DAS) technology. The accurate three-dimensional (3D) position of each ASOC unit is obtained from DAS signals and the prior position information of auxiliary acoustic sources by using a proposed adaptive peak allocation algorithm. Preliminary work has demonstrated single-point 3D localization and distributed ASOC shape detection, and the error is 6.53 cm. To the best of our knowledge, it is the first time that distributed ASOC shape detection is achieved with DAS. This method will promote the development of ASOC applications, such as underwater target detection and towed array correction.

Click detection rate variability of central North Pacific sperm whales from passive acoustic towed arrays.

Passive acoustic monitoring (PAM) is an optimal method for detecting and monitoring cetaceans as they frequently produce sound while underwater. Cue counting, counting acoustic cues of deep-diving cetaceans instead of animals, is an alternative method for density estimation, but requires an average cue production rate to convert cue density to animal density. Limited information about click rates exists for sperm whales in the central North Pacific Ocean. In the absence of acoustic tag data, we used towed hydrophone array data to calculate the first sperm whale click rates from this region and examined their variability based on click type, location, distance of whales from the array, and group size estimated by visual observers. Our findings show click type to be the most important variable, with groups that include codas yielding the highest click rates. We also found a positive relationship between group size and click detection rates that may be useful for acoustic predictions of group size in future studies. Echolocation clicks detected using PAM methods are often the only indicator of deep-diving cetacean presence. Understanding the factors affecting their click rates provides important information for acoustic density estimation.

Optimizing hydrophone-preamplifier systems: Theoretical design, computational analysis, and experimental validation for towed array applications

Hydrophone response parameters greatly influence the design of pre-amplifier and analog to digital conversion (ADC) components. Here, we show a comprehensive methodology for the modeling of hydrophone response, focusing on the theoretical, computational, and experimental approach for low and high frequency SONAR applications. Theoretical calculation of hydrophone response based on electromechanical properties is compared with Finite Element Analysis (FEA) and experimental measurement. An electrical equivalent hydrophone simulator Butterworth-Van Dyke (BVD) circuit is constructed based on admittance and susceptance measurements to represent the transducer's electrical behavior for testing pre-amplifier and ADC response without the presence of environmental or hydrophone noise. This model facilitates a systematic approach to towed array front-end design with hardware in the loop to update models to improve performance prediction. Measurements of the constructed transducer system validate the theoretical and computational models, providing insights into real-world performance.

Influence of bioinspired riblet topographies on the mitigation of flow-induced noise in towed sonar arrays

The hydrodynamic optimization of marine vehicles and devices is a critical area of research, especially regarding the diminution of flow-induced drag pertinent to towed sonar arrays. The utilization of bio-inspired riblets, which emulate the skin of rapid marine predators such as sharks, has been posited as a viable strategy to mitigate hydrodynamic drag. Nonetheless, the implications of these riblets on the concurrent acoustical emissions during flow-array interaction remain not well understood. This study conducts an in-depth investigation into the performance of bioinspired riblet topologies in attenuating flow-induced noise in towed sonar arrays, scrutinizing their effectiveness across laminar and turbulent flow regimes. In laminar flow regimes, the study observes that riblet structures have the potential to reduce noise but at the cost of increased drag for towed arrays. Conversely, in turbulent flow conditions, the effectiveness of riblets is significantly enhanced. Particularly, rectangular riblets demonstrate a notable reduction in noise by up to 14.3%, along with a 5.1% decrease in hydrodynamic drag, in comparison to a smooth array surface. Additionally, our parametric study reveals that riblets with finer, more closely spaced geometries can further reduce the drag by an additional 25.7%. These findings underscore the efficacy of riblet geometries in different flow conditions, highlighting their potential in optimizing the acoustic and hydrodynamic performance of maritime systems.

MTSA-Net: A multiscale time self-attention network for ship radiated self-noise reduction

For a surface ship carrying a towed array, its in-band radiated self-noise is one of the near-field strong interference, which will seriously limit the performance of the underwater acoustic (UWA) signal detection system. Typically, the conventional ship noise cancellation methods requires time-synchronized hydrophone arrays, such as the towed linear array (TLA), to suppress its self-noise by using spatial filters. However, the spatial filter based methods fail when the direction of arrival of the desired signal is in the ship noise masking area. In cooperative scenarios, the prior knowledge of the template signal provides additional temporal information, which can be utilized to design a time-domain representations based detection system. In this paper, a multiscale time self-attention network (MTSA-Net) is proposed to mitigate the ship radiated self-noise and enhance the desired signal to improve the performance of signal detection system. Experimental results based on sea trial data indicate the effectiveness of our proposed method.

Research on Transient Electromagnetic Positioning Method of Underwater Towed Array Source for Moving Small Target on the Seabed

Different from the large-scale delineation and exploration of oil and gas resources and deep-sea hydrothermal sulfide deposits, small targets moving on the seabed require fine and accurate trace detection and higher positioning accuracy. Although the towed single source transient electromagnetic (TEM) device can detect the poisition of the static target body, but cannot determine the poisition of the moving target, the array source TEM device can effectively solve the problem of fine detection and accurate positioning of moving small targets on the seabed, and improve the signal-to-noise ratio and resolution. In this paper, an array source transient electromagnetic positioning method based on underwater towed platform is proposed for moving small targets on the seabed. At the same time, in view of the underwater towed body and array source transient electromagnetic coil, its attitude changes cause the problem of target body positioning error. Through the simulation calculation and error analysis, the results show that the calculation error of attitude angle had a great influence on positioning accuracy. In practical engineering application, attitude correction is necessary to eliminate positioning error.

Source localization in deep water with a towed array from UUV

Unmanned Underwater Vehicle (UUV) can work in larger depth. If a towed array applied on UUV, it can detect the acoustics signals from a target in the direct arrival zone with lower transmission loss in deep water. Based on sound field characteristics in deep water, a source detection scheme with multiple UUVs is proposed. The aperture of sonar array is limited by the carrying capacity of UUV. Therefore, a passive aperture extension with sparse Bayesian learning (SBL) is proposed for a moving short array to improve the performance of direction-of-arrival estimation by constructing a larger virtual aperture. The phase correction factors and bearings of different targets are estimated simultaneously by SBL. The experiment results show that the method extends the aperture effectively and obtains higher azimuth resolution and accuracy for the direction-of-arrival (DOA) estimation than the Conventional Beamforming (CBF). The detection of an underwater target by using a towed array from UUV is possible. [Work supported by the National Natural Science Foundation of China, Grant No. U22A2012.]

Study on the effects of towed array on the resistance and flow characteristics of unmanned underwater vehicle

Unmanned underwater vehicle (UUV) towing a number of trailing bodies carrying detectors as a UUV-towed array system is widely used in fields such as submarine topography exploration, submarine pipeline laying, and submarine energy survey due to its simple structure. This study employs the Computational Fluid Dynamics (CFD) method, using the general submarine models Joubert BB2 and Persia 110 as tug and towing models, to calculate the hydrodynamic performance of the towed system under full control constraints, linear control constraints, and plane control constraints respectively, under the condition of infinite depth and fixed speed. The surrounding flow field velocity under the above three conditions is also analyzed. The study gradually explores the drag and lift of the towed body, the pressure distribution on the surface of the hull, and the force on the catenary, as well as the influence of the towing array on the main UUV and the surrounding flow field. The findings demonstrate that the existence of the towed array system will increase the resistance of the main UUV, with drag movement showing periodic reciprocating motion. Furthermore, the control degree of the towed cable becomes lighter the farther away it is from the main UUV, resulting in a larger range of motion.

A rapid detection method of towed array seismic surface wave for leakage passage of dyke-dam

Rapid detection of leakage passage in dykes has become a committed step in flood prevention work. The seismic surface wave method can be given the S-wave velocity information of the near-surface (≤ 20 m), and qualitatively evaluate the transverse position, depth range, and direction of the leakage passage. The low acquisition efficiency of the cone geophone in the conventional point measurement mode does not meet the requirements of rapid detection. A single survey line has a small coverage area and lacks comparison with neighboring survey lines, so it is not possible to obtain the direction of extension of the leakage passage. In this paper, we propose a rapid detection method of the towed array seismic surface wave for leakage passage of a dyke-dam. Forty-eight gravity geophones are arranged in three columns, 16 in each column, to form the array geometry. Surface wave imaging methods are inversion and fast imaging. The main shortcomings of inversion calculation are (1) lacking shallow information, (2) low vertical resolution, and (3) multiple solutions. To overcome the above issues, the imaging calculation of the surface wave dispersion curve is implemented using fast imaging method. The proposed array geometry is used to collect seismic data. The simulated data and measured data show that fast imaging has the following advantages: (1) It can make full use of the dispersion curve of broadband seismic data, does not lose shallow information, and has high imaging accuracy. (2) It uses the dispersion curve directly for imaging, does not lose any details of velocity changes, and has a high vertical resolution. (3) The imaging results are unique. In contrast to the inversion results, the fast imaging results clearly distinguish the location of the leakage passage and highlight the lateral variability of the leakage passage. The results of the model data and measured data demonstrate the efficiency and high resolution of the towed array seismic geometry and the fast imaging method for leakage passage detection.

Corrigendum: Fast estimation of direction of arrival based on sparse Bayesian learning for towed array sonar during manoeuvring

Corrigendum: Fast estimation of direction of arrival based on sparse Bayesian learning for towed array sonar during manoeuvring

Fast estimation of direction of arrival based on sparse Bayesian learning for towed array sonar during manoeuvring

AbstractFor improving performance of the towed array sonar during the manoeuvring period, a processing framework is proposed based on joint estimation of direction of arrival (DOA) and the array shape. The sparse Bayesian learning (SBL) algorithm is utilised to accurately estimate the DOAs of interesting targets. Meanwhile, the towed array shape is modelled as a parabola array, and the array element positions are estimated using the bow of the parabola. Then, an approximate posterior covariance is implemented to the SBL for a fast converging speed required by practical applications. Besides, the co‐prime array structure is considered for the uniform linear array to further reduce the computational load. The numerical simulations have verified the effectiveness of the fast converging SBL method. MAPEX2000 experimental data processing results have shown that the proposed framework performs well in detection of weak targets during slow turns.

A Linear Near-Field Interference Cancellation Method Based on Deconvolved Conventional Beamformer Using Fresnel Approximation

In underwater acoustic detection using towed arrays, the in-band radiation noise of the tow-ship generates significant interference. In this article, a high-resolution spatial filter based on the deconvolved conventional beamformer (dCv) is proposed to mitigate the impact of this noise on the detection on the beam of interest. The tow-ship interference is near field, thus, the dCv cannot be applied directly as the point spread function is shift variant. In this work, a solution to this problem involving the Fresnel approximation is developed. It is demonstrated analytically that the Fresnel approximation is not sensitive to the accuracy of the estimation of the interference range, and its applicability depends on the arrival angle of the interference. Experimental results show that the linearity of the dCv spatial filter ensures that the amplitude and phase of the array signal can be retrieved with no distortion, which is critical for acoustic detection.

Passive synthetic aperture for direction-of-arrival estimation using sparse Bayesian learning

Passive synthetic aperture (PSA) extension for a moving array has the ability to enhance the accuracy of direction-of-arrival (DOA) estimation by constructing a larger virtual aperture. The array element overlap in array continuous measurements is required for the traditional extended towed array measurement (ETAM) methods. Otherwise, the phase factor estimation is biased, and the aperture extension fails when multiple sources exist. To solve this problem, passive aperture extension with sparse Bayesian learning (SBL) is proposed. In this method, SBL is used to simultaneously estimate the phase correction factors of different targets, followed by phase compensation applied to the extended aperture manifold vectors for DOA estimation. Simulation and experimental data results demonstrate that this proposed method successfully extends the aperture and provides higher azimuth resolution and accuracy compared to conventional beamforming (CBF) and SBL without extension. Compared with the traditional ETAM methods, the proposed method still performs well even when the array elements are not overlapped during the motion.

Impacts of seabed characteristics on short-range acoustic propagation in seismic surveys

An abundance of marine seismic reflection surveys with publicly available datasets have been collected over the last several decades to study the composition of the seabed up to multiple kilometers below the sea floor. In these surveys, a loud impulsive airgun source broadcasts sound into the seabed and the reflections from the seafloor and seabed layers are measured on a long (up to ∼15 km) towed hydrophone array. In these surveys, both the shallow seabed layers (several hundred meters below the seafloor) and deeper layers (multiple kilometers below the seafloor) can significantly impact the acoustic field in the water column at close ranges. Experimental data have shown instances of sound exposure levels (SEL) at ranges between ∼8 and 15 km that exceeded levels predicted by cylindrical spreading models by nearly 15 dB. This work aims to use the abundance of seismic data available to explore the relationship between seabed and sub-seabed characteristics and the acoustic field in the water column. Inversion results that provide seabed sound speed profiles and reflection characteristics will be used to understand the seabed characteristics and its potential effects on SELs or sound pressure levels evaluated along the towed array. [Work supported by ONR.]