Sonar Research Articles

Enhancing underwater target detection: Fusion of spatio‐temporal incompletely‐aligned AIS and sonar information via DTW and multi‐head attention mechanism

AbstractIn the field of underwater target detection, the passive sonar is an important means of long‐distance target detection. The sonar detection information typically includes both surface and underwater targets, whereas it is a great challenge on effectively distinguishing between surface and underwater targets solely based on sonar information. Effective fusion of sonar and AIS (Automatic Identification System) data can leverage their complementary nature to compensate for the limitation of sonar information. However, the sonar information and AIS information are acquired based on different detection principles and systems, which are essentially multi‐source heterogeneous information with obvious spatio‐temporal misalignment in nature. Existing fusion methods normally struggle to effectively align sonar and AIS data in both time and space subject to the complexity of the problem. In this study, the Dynamic Time Warping (DTW) algorithm is applied to align sonar and AIS data in the time domain. In addition, a deep learning algorithm with multi‐head attention mechanism is proposed to achieve the spatial alignment of sonar and AIS data, where the matching between the surface targets in AIS data and the same surface targets in sonar data can also be successfully achieved. It provides a priori knowledge to enhance the underwater target detection of the passive sonar by eliminating the interference of the surface targets. Based on the attention mechanism, the abstract features extracted from the intermediate‐layer of the neural networks are found to be effective to represent the typical features of the target motion trajectories, which also demonstrates the effectiveness of the attention mechanism. The experiment results show that the proposed method can successfully achieve a MatchingSucccessRate of over 95% between the AIS targets and sonar detection targets.

Adaptive Line Enhancer for Passive Sonars Based on Frequency-Domain Sparsity, Shannon Entropy Criterion and Mixed-Weighted Error

AbstractAdaptive line enhancer (ALE) is one of the vital signal processing techniques to the detection and recognition of underwater acoustic targets for passive sonars. Conventional ALEs, based on Gaussian noise assumption and least mean square (LMS) algorithm, can achieve good line enhancement property in Gaussian noise background. However, limited by the high steady-state misadjustment of LMS algorithm, the performance of conventional ALEs deteriorates under non-Gaussian noise background and degrades severely in processing signals with comparably lower signal-to-noise ratio (SNR). Therefore, it’s of great necessity to improve the line enhancement performances of ALE techniques to meet the demands of engineering application in passive sonars. In order to optimize the robustness and adaptability of conventional ALEs in dealing with underwater acoustic signals with much lower-SNR and in non-Gaussian noise background, a modified ALE algorithm called frequency-domain ALE based on l1-norm, Shannon entropy criterion and mixed-weighted norm (l1-SE-MWE-FALE) is proposed in this paper. The proposed l1-SE-MWE-FALE algorithm is based on the integration of frequency-domain sparsity, Shannon entropy (SE) criterion along with mixed-weighted error of LMS and least absolute deviation (LAD) to improve the ALE performance in situations above. The simulation results demonstrate that, when the input SNR is as low as – 25 dB, the local SNR (LSNR) gain for line spectrums by l1-SE-MWE-FALE is 9.8 dB, 3.7 dB and 2.3 dB higher than conventional ALE, l1-norm-based frequency-domain ALE (l1-FALE) and l1 norm-Shannon entropy criterion-based frequency-domain ALE (l1-SE-FALE), respectively. Meanwhile, the simulation results also indicate that the parameters of the proposed method can be chosen loosely and hence are insensitive to the choice of their values. Furthermore, the processing results of two different kinds of real ship-radiated noise signals recorded by passive sonars also imply the advantages of the proposed method over the other three ALEs both qualitatively and quantitatively in the respect of line spectrum LSNR gain and parameter insensitivity. The simulation and experiment results both validate the performance insensitivity to parameter adjustment and hence exhibit a good perspective of applications for passive sonars.

Range-Domain Subspace Detector in the Presence of Direct Blast for Forward Scattering Detection in Shallow-Water Environments

This paper aims to detect a target that crosses the baseline connecting the source and the receiver in shallow-water environments, which is a special scenario for a bistatic sonar system. In such a detection scenario, an intense sound wave, known as the direct blast, propagates directly from the source to the receiver without target scattering. This direct blast usually arrives at the receiver simultaneously with the forward scattering signal and exhibits a larger intensity than the signal, posing a significant challenge for target detection. In this paper, a range-domain subspace is constructed by the horizontal distance between the source/target and each element of a horizontal linear array (HLA) when the ranges of environmental parameters are known a priori. Meanwhile, a range-domain subspace detector based on direct blast suppression (RSD-DS) is proposed for forward scattering detection. The source and the target are located at different positions, so the direct blast and the scattered signal are in different range-domain subspaces. By projecting the received data onto the orthogonal complement subspace of the direct blast subspace, the direct blast can be suppressed and the signal that lies outside the direct blast subspace is used for target detection. The simulation results indicate that the proposed RSD-DS exhibits a performance close to the generalized likelihood ratio detector (GLRD) while requiring less prior knowledge of environments (only known are the ranges of the sediment sound speed and the bottom sound speed), and its robustness to environmental uncertainties is better than that of the latter. Moreover, the proposed RSD-DS exhibits better immunity against the direct blast than the GLRD, since it can still work effectively at a signal-to-direct blast ratio (SDR) of −30 dB, while the GLRD stops working in this case.

Adaptive stochastic resonance enhanced weak linear frequency modulated signal perception in low signal-to-noise ratio environments

Abstract The linear frequency modulated (LFM) signal has gained extensive utilization in radar, sonar and covert communication system due to its large time-bandwidth product, high-precision distance measurement and low detection probability. The perception of weak LMF signals holds significant importance yet encounters substantial challenges within the increasing complexity of the electromagnetic environments. Consequently, this paper proposes an adaptive stochastic resonance (ASR) enhanced approach for perceiving weak LFM signals in low signal-to-noise ratio (SNR) conditions. This approach initially commences a pioneering study on the quantitative synergistic resonance mechanism among LFM signals, random noise, and nonlinear stochastic resonance (SR) systems. Subsequently, the ASR system’s implementation becomes straightforward through the adaptive adjustment of SR system parameters according to the LFM signal and noise characteristics. This implementation leverages the inherent property of noise energy transfer to signal energy, facilitating the enhancement of ordered weak signals via random noise. Following the enhancement of the output signal by the ASR system, the Wigner–Ville distribution (WVD) transform’s time-frequency concentration property is employed to extract the time-frequency characteristics. Building on the WVD transform, the Radon transform with linear integral projection is applied to further harness the time-frequency domain energy concentration, thereby achieving the effective perception of weak LFM signals. Finally, the effectiveness of the proposed method in improving the perception performance of weak LFM signal in very low SNR conditions is verified through numerical simulations. It is anticipated that this method will have potential application value in fields such as radar, sonar, and communication under complex electromagnetic environments.

Interoperable and scalable echosounder data processing with Echopype

Abstract Echosounders are high-frequency sonar systems used to sense fish and zooplankton underwater. Their deployment on a variety of ocean observing platforms is generating vast amounts of data at an unprecedented speed from the oceans. Efficient and integrative analysis of these data, whether across different echosounder instruments or in combination with other oceanographic datasets, is crucial for understanding marine ecosystem response to the rapidly changing climate. Here we present Echopype, an open-source Python software library designed to address this need. By standardizing data as labeled, multi-dimensional arrays encoded in the widely embraced netCDF data model following a community convention, Echopype enhances the interoperability of echosounder data, making it easier to explore and use. By leveraging scientific Python libraries optimized for distributed computing, Echopype achieves computational scalability, enabling efficient processing in both local and cloud computing environments. Echopype’s modularized package structure further provides a unified framework for expanding support for additional instrument raw data formats and incorporating new analysis functionalities. We plan to continue developing Echopype by supporting and collaborating with the echosounder user community, and envision that the growth of this package will catalyze the integration of echosounder data into broader regional and global ocean observation strategies.

Wideband beam domain sparse Bayesian learning passive focusing localisation algorithm

AbstractTo address the challenges of large‐aperture sonar systems passive localisation, this paper proposes the application of sparse Bayesian learning (SBL) for passive target localisation in the wideband beam domain. The proposed algorithm aims to overcome the issues of massive computational requirements for two‐dimensional SBL scanning and increased localisation errors due to interference energy leakage. The wideband beam domain SBL focusing localisation algorithm is developed by constructing an azimuth‐range two‐dimensional transformation matrix to preprocess array data, which effectively reduces the computational load of SBL processing while suppressing strong interference energy leakage in passive sonar operating environments, thus improving the range resolution and parameter estimation accuracy of focusing localisation. Simulation and sea trial data analyses demonstrate the feasibility of the proposed algorithm, with results indicating its superior performance compared to existing algorithms.

Examination of representative manifolds existence in passive sonar dataset

Conventionally, passive sonar classification has been conducted to predict a ship size for given sample. Recent studies have shown high accuracy, far exceeding the performance of early baselines. However, the assumption that manifolds of passive sonar dataset are formed according to the ship size hasn't been studied deeply. In this paper, we investigate the assumption and attempt to analyze the dataset to observe the manifolds. We consider various attributes of passive sonar signals including, which could form the manifold. We employ unsupervised and supervised learning methods with various extracted features. In our analysis, it is difficult to find an attributes dominantly forming the manifolds because passive signals significantly changed by various facts including ocean environment and moving status. Our study wil provide a deeper understanding of the dataset, leading to a realistic and robust passive sonar classifier.

Measurements of temporal variability of acoustic scattering from the seafloor in shallow-water sandy sites.

In the ocean, the performance of active sonar systems depends on the acoustic properties of the seafloor. Daily to monthly variations in near-bottom hydrodynamics and benthic biological activity may affect seafloor properties which then influence the acoustic response of the seafloor. The dependence of seafloor scatter on evolving environmental parameters was investigated using high-frequency active acoustic systems. Seafloor scattering measurements were analyzed in a series of experiments (two weeks to five months in duration) from downward-looking sonars oriented at 20° grazing angle with respect to the seafloor. Data were obtained in two shallow water locations near Portsmouth, New Hampshire, USA: a wave-dominated site and a site dominated by tidal currents. The bottom type for both sites was gravelly sand. The experimental set-up consisted of a tripod placed on the seafloor equipped with three transducers operating at 38, 70, and 200 kHz, a wave-sensing CTD, and underwater cameras. Scattering strength time series were obtained taking into account the local seafloor slope. Results show that there is variability in scattering strength (both in mean levels and distributions). Large variations often coincided with storm events, suggesting that this variability may be driven by changes in bottom roughness caused by storm-related hydrodynamics.

A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division

When a synthetic aperture sonar (SAS) system operates under low-frequency broadband conditions, the azimuth range coupling of the point target reference spectrum (PTRS) is severe, and the high-resolution imaging range is limited. To solve the above issue, we first convert multi-receivers’ signal into the equivalent monostatic signal and then divide the equivalent monostatic signal into range subblocks and the range frequency subbands within each range subblock in order. The azimuth range coupling terms are converted into linear terms based on piece-wise linear approximation (PLA), and the phase error of the PTRS within each subband is less than π/4. Then, we use the chirp-z transform (CZT) to correct range cell migration (RCM) to obtain low-resolution results for different subbands. After RCM correction, the subbands’ signals are coherently summed in the range frequency domain to obtain a high-resolution image. Finally, different subblocks are concatenated in the range time domain to obtain the final result of the whole swath. The processing of different subblocks and different subbands can be implemented in parallel. Computer simulation experiments and field data have verified the superiority of the proposed method over existing methods.

A high-order time-delay difference estimation method for signal enhancement in the distorted towed hydrophone array.

In passive sonar systems, deviations from an ideal linear configuration can significantly impair the beamforming performance of towed hydrophone arrays. This paper presents a method aimed at improving the underwater acoustic signals in the presence of array distortion. The method is centered on a high-order time-delay difference estimation technique utilizing time-frequency autofocus. Initially, a detailed signal model is established that captures the distinctive characteristics of distorted arrays. Subsequently, an algorithm is introduced for high-order time-delay difference estimation to enhance signal fidelity by leveraging phase information within narrowband components originating from incidental acoustic sources. Additionally, a quality metric to evaluate these components is introduced, facilitating the practical implementation of the method. The effectiveness of the proposed approach is validated through both simulation and experimental results, demonstrating its superiority over existing techniques. Importantly, this method does not require prior knowledge of the distortion pattern, making it adaptable to various non-linear array configurations.

Performance During a Task That Simulates Passive Sonar Operator Duties Under Conditions of Varying Workloads.

It is critical to develop and implement lab-based computer experiments that simulate real-world tasks in order to characterize operational requirements and challenges or identify potential solutions. Achieving a high degree of laboratory control, operational generalizability, and ease-of-use for a task is challenging, often leading to the development of tasks that can satisfy some facets but not all. This can result in insufficient solutions that leave real-world stakeholders with unsolved problems. This issue is addressed using a customized passive sonar simulator application that provides extensive researcher control over the design and manipulation of a sonar task; a visual appearance and cognitive demand similar to a true submarine-based sonar task; and a convenient and short training routine for sonar novices. The task requires participants to watch for multiple signal sources of varying appearance and salience and subsequently classify these signals into their respective categories. The current study investigated the effects of stimulus signal strength and signal density on sonar task performance-including metrics of classification accuracy, classification confidence, and response times-finding an interaction between signal density and signal strength that resulted in greater performance errors with high signal density at the weakest signal strength. The lab-based sonar application provides new possibilities for research, not limited to signal intensity and signal density but also through the manipulation of parameters such as the number of unique targets, target appearance, and task duration. This application may illuminate the operational demands that each of these factors may have on operator behavior within the dynamic tasks.

Cascaded-Filter-Based Reverberation Suppression Method of Short-Pulse Continuous Wave for Active Sonar

Reverberation is the main background interference in active sonar and seriously interferes with the extraction of the target echo. Active sonar systems can use short-pulse continuous wave (CW) signals to reduce the reverberation intensity. However, as the pulse width of the CW signals decreases, the reverberation envelope exhibits a high-frequency oscillating phenomenon. Active sonar often uses the cell average constant false alarm ratio (CA-CFAR) method to process the reverberation, which steadily decays with transmission distance. However, the high-frequency oscillation of the reverberation envelope deteriorates the performance of CA-CFAR, which causes a higher false alarm rate. To tackle this problem, the formation mechanism of the high-frequency oscillation characteristics of the reverberation envelope of the short-pulse-width CW signals is modeled and analyzed, and on this basis, an α filter is designed to suppress the high-frequency oscillation of the reverberation envelope before applying CA-CFAR. The simulation and lake trial results indicate that this method can effectively suppress high-frequency oscillations of the reverberation envelope, as well as exhibit robustness and resistance to reverberation interference.

Capacitive Low-Frequency Hydrophone Based on Micronanostructured Iontronic Hydrogel for Underwater Monitoring.

Hydrophones play a crucial role in underwater target detection within sonar systems. However, existing hydrophones often encounter challenges such as low sensitivity and poor signal-to-noise ratio (SNR) in the detection of low-frequency acoustic signals. This work introduces a capacitive hydrophone (CH) designed for highly sensitive detection of low-frequency underwater sound signals. Comprising a latex film/silver electrode and a structured hydrogel as the electrolyte layer, the CH is enclosed in a cylindrical casing. By strategically integrating a carbon nanotube (CNT) topology network within a pyramid microarray in the hydrogel, the sensor efficiently forms the electric double layer (EDL), enhancing sensitivity and precision. The CH showcases exceptional low-pressure sensitivity across a wide frequency spectrum (20 to 800 Hz), achieving a receiving sensitivity of up to -159.7 dB in the critical low-frequency band (20 to 125 Hz), surpassing the performance of the commercial hydrophone (RHC-14) by a substantial margin of 33.29 dB. Furthermore, the CH maintains a superior SNR, enabling the detection of sound waves as faint as 0.3 Pa. This study demonstrates the capabilities of the CH in detecting maritime vessels and underwater sounds, underscoring the potential of the CNT-enhanced EDL sensing mechanism for future low-frequency hydrophone design.

Vibro-acoustic modeling of the turbulent excited cavity-plate-exterior space coupled system

To mitigate flow-induced noise in sonar self-noise, this study introduces a vibro-acoustic modeling technique for sonar cabins. This technique couples a turbulent-flow-excited plate with the interior cavity and the exterior field within a unified model. Employing the Rayleigh-Ritz method, the Chebyshev spectral method, and the Rayleigh integral, the model accounts for general boundary restraints, wall impedances, and reinforcement configurations. Flow-induced responses are determined through the Monte Carlo quadruple integration of frequency response functions and the cross-spectral density model, which characterizes turbulent pressure fluctuations. The convergence and reliability of the present method are verified, achieving excellent agreement with numerical methods and previous results. The study reveals that periodic impedance arrangements in the cavity significantly attenuate sound wave propagation, especially when periodic arrangements are added at low frequencies. The reinforcement configuration perpendicular to the flow direction minimizes low-frequency vibrations. However, the influence of reinforcement on acoustic energy within the cavity is marginal and could potentially lead to increases under simply supported boundary conditions. This method effectively addresses vibro-acoustic challenges in sonar cabins, offering substantial practical value for the development of low-noise sonar systems.

Simulation study on acoustic performance of Tonpilz piezoelectric transducers

Abstract The Tonpilz configuration of transducers is recognized for its capability to generate high-power acoustic emissions at relatively lower frequencies, which is a prevalent setup in sonar systems. Comprising a frontal radiating element, a rear casing, and a piezoelectric ceramic ring sandwiched between them and affixed by a central bolt, this study delineates the inclusion of bolt pretension impact. The investigation assesses the structural and acoustic ramifications of the transducer’s frequency response. These findings indicate the commendable acoustic performance of the transducer.

Use of Sonar Systems to Detect Areas of Gas Discharge of the Seabed

Use of Sonar Systems to Detect Areas of Gas Discharge of the Seabed

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.

Feature Extraction Methods for Underwater Acoustic Target Recognition of Divers.

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.

Optimizing SONAR System Reliability Through RRAP: A Novel Approach Using Opposition Based Levy Flight Moth Flame Optimization

Optimizing SONAR System Reliability Through RRAP: A Novel Approach Using Opposition Based Levy Flight Moth Flame Optimization

DIRECTION OF ARRIVAL ESTIMATION BASED ON SMOOTH MUSIC ALGORITHM COMBINED SPECTRUM SELECTION TECHNIQUES OF NOISE CHARACTERISTICS OF MARINE TARGETS EQUIPPED PROPELLER

This article demonstrates a proposal for a direction of arrival (DOA) estimation algorithm for passive sonar systems based on the combination of the smooth multiple signal classification (Smooth MUSIC) algorithm and frequency bin selection (BS) of the sound of marine propeller-equipped targets, so-called BS-SMUSIC. The harmonics of propeller shaft and blade frequencies are considered useful information for detecting targets and estimating their parameters, including DOA. Low frequency analysis recording (LOFAR) is utilized to implement BS. By analyzing MUSIC-based algorithm together BS, passive DOA estimation algorithms have been significantly improved. Simulation results have been given in both cases: uncorrelated and correlated sources. Outcomes demonstrate that the BS-SMUSIC algorithm has the best performance in comparison to three MUSIC-based algorithms (MUSSIC, Modified MUSIC and Root MUSIC) in all investigation cases: narrow band signals at 5 dB of signal to noise (SNR); wideband signals at -5 dB of SNR. Besides, BS-SMUSIC algorithm also archives the lowest root mean square error (RMSE) in SNR range -5 dB to 20 dB. In the SNR range, the RMSE of BS-SMUSIC algorithm remains stable and is about 0.3 ◦ at -5 dB of SNR. This performance reflects its ability to ensure stable operation, super resolution and high accuracy of BS-SMUSIC algorithm for the passive sonar systems.