This paper presents a comprehensive review of hydrophones, their design considerations, physical aspects, and structures by reviewing many publications that have been published over the last two decades. The investigation of the fundamental aspects and essential considerations of hydrophones in the literature are distributed in different papers and have not been brought together in a conclusive manner. This paper has collected and classified all the information about hydrophones including the parameters that affect their performance as well as their features. We have categorized the hydrophones according to their mechanism of operation, structure design, frequency response, and application. The literature has been summarized in a way that enables the readers' easy referral to appropriate designs for their desired application scenarios.

Hydrophones, fundamental features, design considerations, and various structures: A review

Cymbal transducers are characterized by a high mechanical quality factor and low power efficiency. The research conducted so far on cymbal transducers has focused on improving the power efficiency and structural stability, but modern underwater sensor network systems need transducers to have a wide frequency bandwidth as well. In this study, a wideband cymbal transducer was designed to fill that need. First, the effect of various structural parameters on the performance of the cymbal transducer was analyzed with emphasis on the bandwidth using the finite element method. Based on the analysis results, the structure of the cymbal transducer was optimized to have the widest possible bandwidth while maintaining its transmitting voltage response (TVR) level over a typical power requirement as well. The validity of the design was verified by fabricating a prototype of the optimized cymbal transducer and comparing its measured performance with the design.

https://www.mdpi.com/1424-8220/19/21/4659/pdf

Design and Fabrication of a Wideband Cymbal Transducer for Underwater Sensor Networks.

Received: 18 July 2020 Accepted: 20 December 2020 Background/objectives: The objective of the study is to increase the resolution and radiate sharper beam towards the user in mobile communication using Smart Antenna. Methodology: The Conventional and Subspace Algorithms from the literature are studied and simulated in MATLAB so that the foundation is laid for better detection of algorithms and radiation formation. The results are explained for varying number of antenna elements and mobiles sources placed close to far. Findings: The classical direction of arrival algorithms namely CAPCON, Maximum Entropy Method, Maximum Likelihood Method are used to find the direction of mobile users based on the computation of the power spectrum. Several methods namely Least Mean Square, Griffiths Method, Variable Step Size Griffiths and Recursive Least Square are used to form the main beam for the user detected by the direction of arrival algorithms. Novelty/improvements: In order to take further the research on enhancing the resolution and having a higher convergence rate with reasonable step size, this paper presents the well-known conventional and modern algorithms from the literature. The results are simulated are well described for performing parameters.

Conventional and Subspace Algorithms for Mobile Source Detection and Radiation Formation

In this work, we apply deep learning to estimate the direction-of-arrival (DoA) of multiple narrowband signals with a uniform linear array in a coherent environment. First, the logarithmic eigenvalue-based classification network (LogECNet) is introduced to enhance signal number detection accuracy in challenging scenarios, such as the low signal-to-noise (SNR) regime and limited snapshots. Next, a multi-label classification model called the root-spectrum network (RSNet) is devised to estimate the DoAs using the signal number inferred by LogECNet. In the proposed architecture, the full-row Toeplitz matrices reconstruction (FTMR), which exploits all rows of the signal covariance matrix (SCM), is combined with LogECNet and RSNet to inversely map the SCM to the numerical DoAs in the coherent scenario. It is shown that the eigenvalues factorized from the FTMR output matrix become more robust sources for signal enumeration than those of the forward/backward spatial smoothing (FBSS) algorithm. Furthermore, the logarithmic scaling of the eigenvalues of the FTMR results in LogECNet outperforming other detectors. The simulation results show our proposed method not only improves the signal number detection and angular estimation performance, but also achieves the complexity reduction with respect to the prior schemes.

Deep Learning-Aided Coherent Direction-of-Arrival Estimation With the FTMR Algorithm

This paper reports the performance differences in the receiving sensitivity and band width of Class V flex tensional transducers (Cymbals) both in-air and in-water by varying the design parameters. Cymbal elements with device diameter 8mm and 13mm with optimum designs achieved using finite element software ATILA is presented. The in-air and underwater characteristics of such transducers are described in this paper. The performance evaluation of the transducers both in air and water are also reported in this paper. It has been established that the resonance frequency shifts towards higher side while increasing the cavity depth retaining the cap diameter fixed. However, there exists a tradeoff between the choice of sensitivity and optimum cavity depth. A maximum Receiving Sensitivity (RS) of -203 dB re 1V/µPa @ 1m is obtained analytically for a single element with 13mm diameter and a cavity depth of 600 micron with a band of 2-20 kHz. Also a wide band of 1-30kHz is achieved with 8mm cymbal element having the same cavity depth with a Receiving Sensitivity -202.84 dB re 1V/µPa @ 1m. Effect of encapsulation on the performance of cymbal transducers is studied and analytical results are in agreement with experimental results. There exist critical fabrication factors that affect the performance of these elements while fabricated in bulk quantities for an array. Reliable production procedure has been developed for manufacturing of cymbal elements and its arrays. A 1×3 array of 13mm diameter cymbal transducer has been fabricated and tested for in-air and in-water performances. The RS showed a maximum value of -178 dB re 1V/µPa @ 1m in a frequency range of 2-20 kHz with an in-house developed preamplifier having a gain of 20dB for a single element using brass as cap material. An array gain of nearly 6 dB is obtained when connected in series. The procedure adopted for the fabrication of Cymbal elements is critical for obtaining a flat hydrophone array response over a wide frequency range.

/pdf/performance-evaluation-of-cymbal-hydrophones-for-underwater-sgfrjo3oek.pdf

Performance Evaluation of Cymbal Hydrophones for Underwater Applications

This paper summarizes the effect of manufacturing procedure on the performance of an element as well as an array of cymbal type transducers. A finite element software ATILA, is used to model the cymbal element and optimized the dimension and materials based on the results. A maximum Receiving Sensitivity (RS) of −203 dB re 1V/µPa @ 1m is obtained analytically for a single element with 13mm diameter and a cavity depth of 600 micron and maximum RS of −192 dB re 1V/µPa @ 1m is obtained analytically for a single element with 19mm diameter and a cavity depth of 320 micron. Several prototypes were fabricated and tested the performances in Acoustic Test Facility at NIOT, which is National Accreditation Board of Testing and Calibration of Laboratories (NABL) certified. The RS showed a maximum value of only-182 dB re 1V/µPa @ 1m even with a preamplifier having a gain of 20dB for a 13mm cymbal array (1×5). The experimental results are matching well with modelled results for single elements. But expected array gain as per the numerical calculations were not obtained when connected elements in an array. It has been also observed that the d 33 values of cymbal elements in an array should be identical to get the predicted results. Extreme care should be taken to avoid high pressure from acting upon the apex of the end caps during gluing and other stages. Special care in gluing, blanking and forming operations combined with optimum force/torque is necessary in getting good array performance.

Effect of manufacturing procedure on the miniaturized flextensional transducers (Cymbals) and hydrophone array performance

An indigenously developed Buried Object Detection SONAR (BODS) for finding targets in the seabed is described in this paper. The important features of BODS are wide bandwidth (2–24 kHz), light weight projector (21 kg) and computer based real time signal processing. The results from experiments at shallow waters to detect seabed boundary layer and targets like metal plate and concrete blocks, are also presented in this paper. It is seen that sediment layers and the targets are distinguishable in the BODS image.

Detection of Buried Objects using active Sonar

This paper focuses on the performance of Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance techniques (ESPRIT) algorithm in real-time, for detection of underwater object by active sonar system of frequency 12 kHz. Experiment is conducted in Acoustic tank facility (ATF) at National Institute of Ocean Technology (NIOT). A table with dimension of 0.5mx0.5m is submerged in the tank at a depth of 3.6m from the water surface. A tow body with acoustic transmitter and hydrophone array is used to transmit and receive the acoustic signal in tank. The DOA estimation gives the exact location of the table in the tank. It is observed that the location of the submerged table computed by MUSIC & ESPRIT is comparable with a bias of about 1 degree.

Experimental observation of direction-of-arrival (DOA) estimation algorithms in a tank environment for sonar application

Context is an important aspect for accurate saliency detection. However, the question of how to formally model image context within saliency detection frameworks is still an open problem. Recent saliency detection models designed using complex Deep Neural Networks to extract robust features, however often fail to select the right contextual features. These methods generally utilize physical attributes of objects for generating final saliency maps, but ignores scene contextual information. In this paper, we overcome such limitation using (i) a proposed novel end-to-end framework with a Contextual Unit (CTU) module that models the scene contextual information to give efficient saliency maps with the help of Convolutional GRU (Conv-GRU). This is the first work reported so far that utilizes Conv-GRU to generate image saliency maps. In addition, (ii) we propose a novel way of using the Conv-GRU that helps to refine saliency maps based on input image context. The proposed model has been evaluated on challenging benchmark saliency datasets, where it outperforms prominent state-of-the-art methods.

Shibu Jacob

Papers

Performance Evaluation of Cymbal Hydrophones for Underwater Applications

Effect of manufacturing procedure on the miniaturized flextensional transducers (Cymbals) and hydrophone array performance

Detection of Buried Objects using active Sonar

Experimental observation of direction-of-arrival (DOA) estimation algorithms in a tank environment for sonar application

Visual Saliency Detection via Convolutional Gated Recurrent Units