Sonar Detection Research Articles

Three Dimensional Volume Coverage in Multistatic Sonar Sensor Networks

Recent changes in the design of enemy threats such as submarines and the technological achievements in sensor development have paved the way for multistatic sonar applications, which increase security and situational awareness in underwater tactical operations. Previously, coverage in multistatic sonar sensor networks (MSSN) was studied using Cassini ovals and the traditional sonar detection model in two dimensions without any discussion of the practicability and feasibility in terms of conditions related to the underwater acoustic propagation environment. In this study, a practical three-dimensional MSSN channel model is proposed. The proposed model covers a spectral variation of absorption loss, ambient noise, sound speed profile, and shadow zones. The realistic effects of sound propagation and environmental conditions are modeled and evaluated using Lybin, which is a well-known sonar performance prediction tool. Using the practical MSSN channel model, the number of source-receiver pairs required to cover a three-dimensional MSSN volume is calculated. The impacts of frequency, source-to-receiver distance, and source level are investigated. The results are compared to the Cassini oval and traditional sonar detection models via an error expression derived according to our verified practical model. The results reveal that the inclusion of ambient conditions and sound propagation characteristics in the channel model leads to huge error levels of 4700000% in the Cassini oval model and 170000% in the traditional sonar detection model, depending on frequency. Thus, the applicability of these models in realistic MSSN deployment scenarios is limited.

Effect of background clutter on neural discrimination in the bat auditory midbrain.

The discrimination of complex sounds is a fundamental function of the auditory system. This operation must be robust in the presence of noise and acoustic clutter. Echolocating bats are auditory specialists that discriminate sonar objects in acoustically complex environments. Bats produce brief signals, interrupted by periods of silence, rendering echo snapshots of sonar objects. Sonar object discrimination requires that bats process spatially and temporally overlapping echoes to make split-second decisions. The mechanisms that enable this discrimination are not well understood, particularly in complex environments. We explored the neural underpinnings of sonar object discrimination in the presence of acoustic scattering caused by physical clutter. We performed electrophysiological recordings in the inferior colliculus of awake big brown bats, to broadcasts of prerecorded echoes from physical objects. We acquired single unit responses to echoes and discovered a subpopulation of IC neurons that encode acoustic features that can be used to discriminate between sonar objects. We further investigated the effects of environmental clutter on this population's encoding of acoustic features. We discovered that the effect of background clutter on sonar object discrimination is highly variable and depends on object properties and target-clutter spatiotemporal separation. In many conditions, clutter impaired discrimination of sonar objects. However, in some instances clutter enhanced acoustic features of echo returns, enabling higher levels of discrimination. This finding suggests that environmental clutter may augment acoustic cues used for sonar target discrimination and provides further evidence in a growing body of literature that noise is not universally detrimental to sensory encoding.NEW & NOTEWORTHY Bats are powerful animal models for investigating the encoding of auditory objects under acoustically challenging conditions. Although past work has considered the effect of acoustic clutter on sonar target detection, less is known about target discrimination in clutter. Our work shows that the neural encoding of auditory objects was affected by clutter in a distance-dependent manner. These findings advance the knowledge on auditory object detection and discrimination and noise-dependent stimulus enhancement.

The Altes Family of Log-Periodic Chirplets and the Hyperbolic Chirplet Transform

This work revisits a class of biomimetically inspired waveforms introduced by R.A. Altes in the 1970s for use in sonar detection. Similar to the chirps used for echolocation by bats and dolphins, these waveforms are log-periodic oscillations, windowed by a smooth decaying envelope. Log-periodicity is associated with the deep symmetry of discrete scale invariance in physical systems. Furthermore, there is a close connection between such chirping techniques, and other useful applications such as wavelet decomposition for multi-resolution analysis. Motivated to uncover additional properties, we propose an alternative, simpler parameterisation of the original Altes waveforms. From this, it becomes apparent that we have a flexible family of hyperbolic chirps suitable for the detection of accelerating time-series oscillations. The proposed formalism reveals the original chirps to be a set of admissible wavelets with desirable properties of regularity, infinite vanishing moments and time-frequency localisation. As they are self-similar, these “Altes chirplets” allow efficient implementation of the scale-invariant hyperbolic chirplet transform (HCT), whose basis functions form hyperbolic curves in the time-frequency plane. Compared with the rectangular time-frequency tilings of both the conventional wavelet transform and the short-time Fourier transform, the HCT can better facilitate the detection of chirping signals, which are often the signature of critical failure in complex systems. A synthetic example is presented to illustrate this useful application of the HCT.

Experimental investigation of bubble formation and motion mechanism near the moonpool

When a research ship sails at a high speed, there is relative motion between the ship and fluid. The ship is slammed by the fluid. To reduce the direct impact of the fluid, sonar is installed in the moonpool, and acoustic detection equipment is installed along the research ship bottom behind the moonpool. However, during high-speed sailing, a large number of bubbles form in the moonpool. Some bubbles escape from the moonpool and flow backward along the bottom of the ship. When a large number of bubbles are around the sonar and acoustic detection equipment, the equipment malfunctions. However, there have been few studies on bubble formation in the moonpool with sonar and distribution along the ship bottom behind the moonpool. Therefore, a related model was developed and prototype tests were carried out in this study. The appropriate similarity criteria were selected and verified to ensure the reliability of the experiment. Considering the influences of speed, sonar, moonpool shape, and draft, the reason and mechanism of bubble formation in a sonar moonpool were studied. An artificial ventilation method was used to simulate a real navigation environment. Because the bubbles are in a bright state under laser irradiation, the bubbles can be used as tracer particles. A high-speed camera captured illuminated bubbles. The distribution mechanism of bubbles along the ship bottom behind the moonpool was investigated using particle image velocimetry under the influence of the moonpool shape and sailing speed. The model experimental results agreed well with those of the prototype test. The air sucked into the water was the dominant factor in bubble formation in the moonpool. The bubbles were distributed in a W shape under the ship bottom.

Numerical Study on Multiple-Blade-Rate Unsteady Propeller Forces for Underwater Vehicles

_ The unsteady propeller forces of an underwater vehicle were numerically simulated using computational fluid dynamics to investigate the effects of the axial location of the stern planes. A benchmark study was undertaken using a three-bladed propeller; experimental results of the nominal inflow wake profile were analyzed and the unsteady propeller forces were measured. The numerical method was applied to predict the unsteady propeller forces in the SUBOFF model’s wake by varying the axial locations of the stern planes. Several remarks were made on the primary harmonics of the hull’s wakes and blade-rate propeller forces. Introduction The hydroacoustic noise, which matches multiples of the number of propeller blades and its rotational speed, known as “blade-rate (BR) noise,” has been increasingly used to manage hydroacoustics for naval vessels. BR noise can be caused by alternating blade loads owing to fluctuations in the angle of attack of the blades because marine propellers are operated in the nonuniform wake of ships’ hulls. The unsteady blade load produces unsteady propeller forces that are transmitted via the propeller shaft and bearing, thus producing undesirable vibration and noise. Although the resultant BR noise is a common issue for marine vessels, in particular, submarines and other underwater vehicles deployed for undersea defense systems and oceanographic survey systems require strict specifications for the acoustic signature. Therefore, the unsteady propeller forces must be improved for reduced detectability, because the vehicles should be able to operate without being discovered while sonar detection technology continues to improve.

Distributed MIMO sonar for detection of moving targets in shallow sea environments

A joint processing framework is proposed for distributed multiple-input-multiple-output (MIMO) sonar systems to exploit spatial diversity and array gain for detection of moving targets. An extended moving target consisting of multiple scatterers is illuminated by widely-spaced transmitters from different angles to achieve spatial diversity. Target bearing is first estimated with high resolution by the deconvolved conventional beamforming technique. Then a replica correlation integration processor is utilized to estimate the target’s range and speed in a multipath propagation environment. A MIMO detector is designed with the estimated target position parameters and Doppler factor under the generalized likelihood ratio test framework. The effectiveness of the distributed MIMO sonar system has been validated by the localization of two moving targets in sea experiments.

A denoising algorithm for linear frequency modulation signal based on window function and empirical mode decomposition

The linear frequency modulation signal is widely used in radar, sonar detection and communications as a typical non-stationary signal. In order to better analyse the linear frequency modulation signal received by the receiver, it is necessary to perform denoising processing on the received signal. As a new type of time-frequency analysis method, empirical mode decomposition algorithm is very suitable for processing non-stationary signals. However, due to the large bandwidth of the linear frequency modulation signal, more noise will be retained when the traditional empirical mode decomposition algorithm is used to denoise the linear frequency modulation signal. Under above background, this paper proposes a denoising method based on the window function and the empirical mode decomposition to achieve further denoising of the linear frequency modulation signal. According to the simulation results, when the signal-to-noise ratio is about 0dB, the method proposed in this paper improves the signal-to-noise ratio by about 1.5dB compared with the traditional empirical modal decomposition algorithm.

Spatial and seasonal variations in surface water temperature and salinity in the Mexico‐Belize riverine estuary: Possible comfort conditions for manatees?

AbstractThe Mexican Caribbean and Belize are home to one of the largest populations of Caribbean manatees (Trichechus manatus manatus). However, the transboundary Hondo River estuary is less examined compared to the surrounding protected areas. This paper provides a quantitative description of the spatial and temporal variability in abiotic factors and manatee distribution throughout the Hondo River estuary, with monthly field measurements during 2018–2019. Simultaneously, visual observations and side‐scan sonar detection were implemented, with 84 manatee sightings reported (calves 11.9%, noncalves 88.1%). Heatmap and frequency analyses showed that most manatee sightings occurred at the riverine estuary limit, the confluences between the river and the bay into which it flows. The surface water temperature and salinity ranged 28°C ≤ T ≤ 32°C and 0.5 PSU ≤ S ≤ 4.5 PSU for ~72% of the manatees identified, potentially describing locally preferred conditions for manatees. During the regional mid‐summer drought, higher temperature (31.5°C), salinity (18 PSU), and estuary extent (17.6 km) were recorded, including the maximum peak of manatee sightings (~31%). The roles of these abiotic factors are discussed as tentative environmental comfort conditions for manatees that could reduce their energy and maintenance costs. The identification of preferred conditions could broaden perspectives on how manatees interact with their habitats.

On the Bandwidth and Beam Profile Characteristics of a Simple Low-Frequency Collimated Ultrasound Beam Source

Abstract We numerically investigate the bandwidth and collimation characteristics of ultrasound beams generated by a simple collimated ultrasound beam source that consists of a piezoelectric disk operated near its radial mode resonances. We simulate the ultrasound beam generated in a fluid medium as a function of the excitation frequency for two cases: (1) free piezoelectric disk that corresponds to zero-traction along the lateral edge and (2) fixed piezoelectric disk that corresponds to zero-displacement along the lateral edge. We present and discuss the physical mechanism underpinning the frequency-dependent collimation and bandwidth properties of the ultrasound beams. We observe that the collimated beam generated by the free disk repeatedly lengthens/shortens and also extends/retracts sidelobes with increasing frequency. Alternatively, fixing the piezoelectric disk results in a consistent beam profile shape across a broad range of frequencies. This facilitates generating broadband signals such as a Gaussian pulse or chirp, which are common in ultrasound imaging. Thus, the fixed piezoelectric disk finds application as a collimated ultrasound beam source in a wide range of applications including medical ultrasound imaging, scanning acoustic microscopy, sonar detection, and other nondestructive ultrasound inspection techniques.

Underwater reverberation suppression based on non-negative matrix factorisation

Reverberation is the main background interference in underwater active sonar target detection that seriously interferes with the extraction of the target highlight echo. In consideration of the difference in the time-frequency distributions of the target highlight echo and reverberation, an underwater reverberation suppression method based on non-negative matrix factorisation is proposed in this study. The Wigner-Ville time-frequency matrix of the underwater target echo is used as the input, and non-negative matrix factorisation is applied to express the time-frequency matrix as a low-rank matrix. The influences of rank selection on the reverberation suppression effect and signal expression of the target highlight echo are analysed. Given that the time-frequency matrix of the target highlight echo cannot be expressed in the low-rank form when transmitting linear frequency modulation signal, this matrix is processed with low-rank preprocessing through matrix rotation. The components of the target highlight echo, which can be expressed in the form of a low-rank matrix, are preserved. By contrast, the components of the reverberation interference, which cannot be represented in such a form, are removed in the underwater target echoes. The simulation and experimental results show that the algorithm can effectively improve the signal-to-reverberation ratio of underwater target echoes.

Horizontal Correlation of Long-Range Bottom Reverberation in Shallow Sloping Seabed

The performance of active sonar detection systems is seriously affected by the reverberation at the bottom of the waveguide in shallow water. In order to improve the performance of active sonar detection, it is necessary to understand the horizontal correlation of shallow-water bottom reverberation in active towed-array processing technology. However, the current research on the spatial correlation of reverberation is mainly based on vertical correlation, little work has been done on the horizontal correlation characteristics of long-distance seabed reverberation, and there is no support from sea test data. In this paper, the coupled mode reverberation model is applied to the horizontal correlation, and is studied according to the receiving position, time, and frequency. The simulation results show that, for the long-range bottom reverberation, the lateral correlation is greater than the longitudinal correlation in the horizontal space. By introducing the adiabatic mode solution, the mathematical model of horizontal correlation in the range-dependent waveguide with depth is derived. The numerical results show that the influence of the seabed dip angle on the horizontal correlation should be considered and that the horizontal correlation is affected obviously by the propagation effects of the sloped sea floor. Finally, the experimental data processing and analysis are given and verify the correctness of the algorithm.

Design and Experiments of a Portable Seabed Integrated Detection Sonar.

The integrated observation of seabed topography, sediment geomorphology and sub-bottom profile information is very important for seabed remote sensing and mapping. To improve the efficiency of seabed detection and meet the needs of portable development of detection equipment, we developed a portable seabed feature integrated detection sonar (PSIDS) with whcih a single sonar device can simultaneously detect the above three types of seabed information. The underwater transducer is mainly composed of the following three components: a parametric emission array as the sound source, a high frequency receiving linear array for multibeam echo signal collection, and a two-dimensional vector hydrophone for receiving the low-frequency sediment echo signal. Field experiments were conducted to validate the performance of the PSIDS on 11–17 January 2018 in Jiaozhou Bay, China. (1) PSIDS could perform the functions of both multibeam sonar and sub-bottom profiler; (2) The synchronously and integrated measurement of various seabed information was achieved by alternately emitting multibeam echo-sounding and sub-bottom profiling signal using parametric source. The detection results proved the feasibility and practicability of PSIDS to achieve multiple seafloor characteristics. PSIDS provides a new idea for developing integrated seabed detection sonar. In terms of convenience and data fusion, it is a good option to use this equipment for integrated seabed detection.

Research on Lightweight Improvement of Sonar Image Classification Network

According to the constructed sonar common target detection dataset derived classification dataset, the convolutional neural network is used to classify the target. And in order to be able to better apply actual engineering, the lightweight of the network has been studied in depth. First, the performance of the ordinary convolutional neural network VGG-16 and the lightweight convolutional neural network MobileNet on the derived classification dataset is compared. The results show that the lightweight network achieves better results at a smaller cost. Then use the dilated convolution and bottleneck structure to improve the MobileNet network to obtain the IMDNet network and the IMBNet network. Through experimental comparison and analysis, the two improved networks have a significant reduction in the amount of parameters and calculations compared to the MobileNet network. The performance of the IMBNet network is basically the same as that of the MobileNet network, and the accuracy of the IMDNet network is 2.02% higher than that of the MobileNet network. This shows that in the field of sonar image classification research, lightweight convolutional neural networks have good performance, and have certain practical application prospects and values.

Research on Penetration Path Planning Method on Near Sea Bottom Based on the Sonar Detection Blind Zone

To improve the survivability and penetration probability of unmanned undersea vehicle(UUV) on near sea bottom combat missions, the factors leading to sonar detection blind zone are analyzed, and the detection blind zone produced by underwater terrain obscuration is mainly studied. A detection range calculation method based on DEM and acoustic ray is proposed, and the simulation study of the near sea bottom penetration path planning is carried out by using terrain blind zone and invasive weed optimization algorithm. Simulation results show the effectiveness of the proposed algorithm. This method can be applied to path planning of the UUV on near sea bottom penetration, which helps to improve Combat effectiveness and Operational effectiveness of UUV.

Sonar Image Target Detection and Recognition Based on Convolution Neural Network

Recent advancements in deep learning offer an effective approach for the study in machine vision using optical images. In this paper, a convolution neural network is used to deal with the target task of sonar detection, and the performance of each neural network model in the sonar image detection and recognition task of underwater box and tire is compared. The simulation results show that the neural network method proposed in this paper is better than the traditional machine learning methods and SSD network models. The average accuracy of the proposed method for sonar image target recognition is 93%, and the detection time of a single image is only 0.3 seconds.

Bottom Detection from Backscatter Data of Conventional Side Scan Sonars through 1D-UNet

As widely applicated in many underwater research fields, conventional side-scan sonars require the sonar height to be at the seabed for geocoding seabed images. However, many interference factors, including compensation with unknown gains, suspended matters, etc., would bring difficulties in bottom detection. Existing methods need manual parameter setups or to use postprocessing methods, which limits automatic and real-time processing in complex situations. To solve this problem, a one-dimensional U-Net (1D-UNet) model for sea bottom detection of side-scan data and the bottom detection and tracking method based on 1D-UNet are proposed in this work. First, the basic theory of sonar bottom detection and the interference factors is introduced, which indicates that deep learning of the bottom is a feasible solution. Then, a 1D-UNet model for detecting the sea bottom position from the side-scan backscatter strength sequences is proposed, and the structure and implementation of this model are illustrated in detail. Finally, the bottom detection and tracking algorithms of a single ping and continuous pings are presented on the basis of the proposed model. The measured side-scan sonar data in Meizhou Bay and Bayuquan District were selected in the experiments to verify the model and methods. The 1D-UNet model was first trained and applied with the side-scan data in Meizhou Bay. The training and validation accuracies were 99.92% and 99.77%, respectively, and the sea bottom detection accuracy of the training survey line was 99.88%. The 1D-UNet model showed good robustness to the interference factors of bottom detection and fully real-time performance in comparison with other methods. Moreover, the trained 1D-UNet model is used to process the data in the Bayuquan District for proving model generality. The proposed 1D-UNet model for bottom detection has been proven effective for side-scan sonar data and also has great potentials in wider applications on other types of sonars.

Sonar image reconstruction method based on adaptive compensation of very shallow water acoustic channel features

Aiming at the problem of eliminating the influence of channel interference on the detection results in the process of using sonar to detect very shallow water targets, a sonar image reconstruction method based on adaptive compensation of very shallow water acoustic channel features is proposed. Standard acoustic source and remote server are used to complete the adaptive calibration process of channel characteristic parameters before detection. The calibrated channel characteristic parameters are used in the subsequent beamforming algorithm to compensate the channel interference. The time-of-flight parameters calculated by the compensation algorithm are used in the subsequent point cloud generation and image reconstruction. Simulation and field test show that the proposed compensation method can improve sonar target detection ability by 25% in very shallow water and complex acoustic channel environment, and the quality of sonar image reconstruction is significantly improved.

Reducing bubble generation and sweepdown effect on a research vessel with a moonpool

Some research vessels set moonpools for sonars installation. The moonpool provides a relatively good working environment for sonar in a harsh marine environment. At the same time, other acoustic detection equipment are installed along the ship bottom behind the moonpool. Due to the exist of the sonar with a variable cross-section, the number of bubbles generated in the moonpool increases. The bubbles generated in the moonpool expel and flow along the vessel bottom to the stern, which leads to the sweepdown effect. The performance of the sonar and other acoustic detection equipment degrades by the bubbles around. However, the research on reducing bubble generation in the moonpool and sweepdown effects is rare. So in present paper the reduction effects of damping devices such as the flange and choke deck on the bubble generation in the moonpool are investigated experimentally. Then, in order to reduce the sweepdown effects of bubbles on the ship bottom, three other damping devices which are double flaps, diversion channel and wedge are investigated. It can be seen that through reducing the area of bubble leakage in the moonpool the distribution position of bubbles can be effectively restricted and the width and thickness of the bubbles reduce.

Structural Design and Physical Mechanism of Axial and Radial Sandwich Resonators with Piezoelectric Ceramics: A Review.

Piezoelectric ceramics are inexpensive functional materials which are widely used in sonar detection, home appliances, meteorological detection, telemetry and environmental protection and other applications. Sensors fabricated from these materials are compact and have fast response characteristics. Their underlying functional methodology is based on the direct piezoelectric effect whereby very small mechanical vibration signals are converted into electrical signals. Piezoelectric resonators are based on the reverse piezoelectric effect and they are widely used for the control of precision instruments and precision machinery, microelectronic components, bioengineering devices and other in applications requiring components to provide precision control of the relevant functional mechanism. In this paper, the structural evolution and design mechanism of sandwich resonators based on piezoelectric materials are reviewed, and the advantages and disadvantages of different structures are compared and analyzed. The goal is to provide a comprehensive reference for the selection, application and promotion of piezoelectric resonators and for future structural innovation and mechanism research relevant to sandwich resonators.

Method to Determinate Surveying Ship Dynamic Draft and Error

In order to improve the accuracy of the MBES(multi-beam echosounding system), and determine the dynamic draft and error magnitude of the surveying ship, the multi-beam sonar detection method and GPS dynamic positioning are used for the water depth and GPS elevation data at different ship speeds in the same area. The method measures the dynamic draft correction magnitude, and the calculation with the error, which verifies the feasibility of the method, provides reliable dynamic draft and error magnitude for multi-beam data post-processing, and improves data accuracy.