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Underwater Acoustics Modelling and Control
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Underwater Acoustics Modelling and Control

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 12208

Special Issue Editors

Dr. Tongrui Peng

E-Mail Website
Guest Editor
College of Science, Shanghai Institute of Technology, Shanghai 201418, China
Interests: active noise control; assistive robotics; adaptive control; nonlinear systems modeling and controlling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mohammad Osman Tokhi

E-Mail Website
Guest Editor
School of Engineering, London South Bank University, London SE1 0AA, UK
Interests: active noise and vibration control; adaptive/intelligent control; soft-computing modeling and control of dynamic systems; assistive robotics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Li Ma

E-Mail Website
Guest Editor
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Interests: underwater sound propagation; acoustic reverberation; ocean noise; seabed acoustic
Dr. Lingzhong Guo

E-Mail Website
Guest Editor
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK
Interests: spatio-temporal/infinite-dimensional system identification and analysis in the space and time domain and the frequency domain; multiscale modelling of biomedical systems; modelling and analysis of differentially expressed genes in biology; barrel cortex local field potential (LFP) modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Noise is defined as unwanted sound (acoustics) and underwater noise pollution is gradually being recognized as a significant threat to aquatic ecosystems. Underwater noise pollution refers to human-generated noise that contaminates our oceans and their habitats, e.g., many marine mammals and corals. There are four main sources of underwater noise, seismic air gun noise from oil and gas exploration, shipping traffic noise, low-frequency and the mid-frequency sonar ‘sounds’ used extensively in submarine detection, and explosive noise.

Modelling is a powerful technique for humans to represent a real-world object or phenomenon and the mental model, the graphical model and the mathematical model are three popular models. Generally, there are two predominant approaches to build a model, the theoretical approach that derives equations from physics and the experimental approach that derives equations from input/output measured data.

Control is a way to amend the system’s performance through adding functional components and acoustical control can be implemented at three points, at the acoustic source, during the propagation path, and in the acoustic receiver.

This Special Issue will collect the latest high-quality original manuscripts within the research field of underwater noise modelling and control. Authors are invited to present new modelling and control techniques, algorithms, and experimental tests. All original papers related to modelling and control techniques for underwater noise are welcome. Both original research and review articles are all encouraged.

Potential topics include but are not limited to the following:

  • Underwater acoustics instrument
  • The application of unmanned vehicle in underwater acoustics measurement
  • Underwater wave propagation
  • Underwater noise modelling
  • Underwater acoustic communication
  • Sonar system
  • System identification
  • Adaptive underwater noise control
  • Intelligent systems
  • Optimization algorithms
  • Underwater acoustic sensor networks

Dr. Tongrui Peng
Prof. Dr. M. Osman Tokhi
Prof. Dr. Li Ma
Dr. Lingzhong Guo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Underwater acoustics instrument
  • Underwater acoustic communication channel modelling
  • Underwater noise modelling
  • Sonar system
  • System identification
  • Adaptive underwater noise control
  • Intelligent systems
  • Optimization algorithms
  • Underwater acoustic sensor networks

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Published Papers (5 papers)

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Research

13 pages, 1390 KiB  
Article
Coded-GFDM for Reliable Communication in Underwater Acoustic Channels
by Mohsin Murad, Imran A. Tasadduq and Pablo Otero
Sensors 2022, 22(7), 2639; https://doi.org/10.3390/s22072639 - 30 Mar 2022
Cited by 7 | Viewed by 2295
Abstract
The performance of the coded generalized frequency division multiplexing (GFDM) transceiver has been evaluated in a shallow underwater acoustic channel (UAC). Acoustic transmission is the scheme of choice for communication in UAC since radio waves suffer from absorption and light waves scatter. Although [...] Read more.
The performance of the coded generalized frequency division multiplexing (GFDM) transceiver has been evaluated in a shallow underwater acoustic channel (UAC). Acoustic transmission is the scheme of choice for communication in UAC since radio waves suffer from absorption and light waves scatter. Although orthogonal frequency division multiplexing (OFDM) has found its ground for multicarrier acoustic underwater communication, it suffers from high peak to average power ratio (PAPR) and out of band (OOB) emissions. We propose a coded-GFDM based multicarrier system since GFDM has a higher spectral efficiency compared to a traditional OFDM system. In doing so, we assess two block codes, namely Bose, Chaudari, and Hocquenghem (BCH) codes, Reed-Solomon (RS) codes, and several convolutional codes. We present the error performances of these codes when used with GFDM. Furthermore, we evaluate the performance of the proposed system using two equalizers: Matched Filter (MF) and Zero-Forcing (ZF). Simulation results show that among the various block coding schemes that we tested, BCH (31,6) and RS (15,3) give the best error performance. Among the convolutional codes that we tested, rate 1/4 convolutional codes give the best performance. However, the performance of BCH and RS codes is much better than the convolutional codes. Moreover, the performance of the ZF equalizer is marginally better than the MF equalizer. In conclusion, using the channel coding schemes with GFDM improves error performance manifolds thereby increasing the reliability of the GFDM system despite slightly higher complexity. Full article
(This article belongs to the Special Issue Underwater Acoustics Modelling and Control)
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14 pages, 1278 KiB  
Article
Recovering the Free-Field Acoustic Characteristics of a Vibrating Structure from Bounded Noisy Underwater Environments
by Wei Lin and Sheng Li
Sensors 2021, 21(16), 5521; https://doi.org/10.3390/s21165521 - 17 Aug 2021
Cited by 1 | Viewed by 1715
Abstract
The vibrational behavior of an underwater structure in the free field is different from that in bounded noisy environments because the fluid–structure interaction is strong in the water and the vibration of the structure caused by disturbing fields (the reflections by boundaries and [...] Read more.
The vibrational behavior of an underwater structure in the free field is different from that in bounded noisy environments because the fluid–structure interaction is strong in the water and the vibration of the structure caused by disturbing fields (the reflections by boundaries and the fields radiated by sources of disturbances) cannot be ignored. The conventional free field recovery (FFR) technique can only be used to eliminate disturbing fields without considering the difference in the vibrational behavior of the structure in the free field and the complex environment. To recover the free-field acoustic characteristics of a structure from bounded noisy underwater environments, a method combining the boundary element method (BEM) with the vibro-acoustic coupling method is presented. First, the pressures on the measurement surface are obtained. Second, the outgoing sound field and the rigid body scattered sound field are calculated by BEM. Then, the vibro-acoustic coupling method is employed to calculate the elastically radiated scattered sound field. Finally, the sound field radiated by the structure in the free field is recovered by subtracting the rigid body scattered sound field and the elastically radiated scattered sound field from the outgoing sound field. The effectiveness of the proposed method is validated by simulation results. Full article
(This article belongs to the Special Issue Underwater Acoustics Modelling and Control)
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13 pages, 2474 KiB  
Communication
Energy-Efficient Time Synchronization Based on Nonlinear Clock Skew Tracking for Underwater Acoustic Networks
by Di Liu, Min Zhu, Dong Li, Xiaofang Fang and Yanbo Wu
Sensors 2021, 21(15), 5018; https://doi.org/10.3390/s21155018 - 23 Jul 2021
Cited by 2 | Viewed by 1976
Abstract
Time synchronization plays an important role in the scheduling and position technologies of sensor nodes in underwater acoustic networks (UANs). The time synchronization (TS) algorithms face challenges such as high requirements of energy efficiency, the estimation accuracy of the time-varying clock skew and [...] Read more.
Time synchronization plays an important role in the scheduling and position technologies of sensor nodes in underwater acoustic networks (UANs). The time synchronization (TS) algorithms face challenges such as high requirements of energy efficiency, the estimation accuracy of the time-varying clock skew and the suppression of the impulsive noise. To achieve accurate time synchronization for UANs, an energy-efficient TS method based on nonlinear clock skew tracking (NCST) is proposed. First, based on the sea trial temperature data and the crystal oscillators’ temperature–frequency characteristics, a nonlinear model is established to characterize the dynamic of clock skews. Second, a single-way communication scheme based on a receiver-only (RO) paradigm is used in the NCST-TS to save limited energy. Meanwhile, impulsive noises are considered during the communication process and the Gaussian mixture model (GMM) is employed to fit receiving timestamp errors caused by non-Gaussian noise. To combat the nonlinear and non-Gaussian problem, the particle filter (PF)-based algorithm is used to track the time-varying clock state and an accurate posterior probability density function under the GMM error model is also given in PF. The simulation results show that under the GMM error model, the accumulative Root Mean Square Errors (RMSE) of NCST-TS can be reduced from 10−4 s to 10−5 s compared with existing protocols. It also outperforms the other TS algorithms in the aspect of energy efficiency. Full article
(This article belongs to the Special Issue Underwater Acoustics Modelling and Control)
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21 pages, 1345 KiB  
Article
Bayesian Learning-Based Clustered-Sparse Channel Estimation for Time-Varying Underwater Acoustic OFDM Communication
by Shuaijun Wang, Mingliu Liu and Deshi Li
Sensors 2021, 21(14), 4889; https://doi.org/10.3390/s21144889 - 18 Jul 2021
Cited by 8 | Viewed by 2466
Abstract
Orthogonal frequency division multiplexing (OFDM) has been widely adopted in underwater acoustic (UWA) communication due to its good anti-multipath performance and high spectral efficiency. For UWA-OFDM systems, channel state information (CSI) is essential for channel equalization and adaptive transmission, which can significantly affect [...] Read more.
Orthogonal frequency division multiplexing (OFDM) has been widely adopted in underwater acoustic (UWA) communication due to its good anti-multipath performance and high spectral efficiency. For UWA-OFDM systems, channel state information (CSI) is essential for channel equalization and adaptive transmission, which can significantly affect the reliability and throughput. However, the time-varying UWA channel is difficult to estimate because of excessive delay spread and complex noise distribution. To this end, a novel Bayesian learning-based channel estimation architecture is proposed for UWA-OFDM systems. A clustered-sparse channel distribution model and a noise-resistant channel measurement model are constructed, and the model hyperparameters are iteratively optimized to obtain accurate Bayesian channel estimation. Accordingly, to obtain the clustered-sparse distribution, a partition-based clustered-sparse Bayesian learning (PB-CSBL) algorithm was designed. In order to lessen the effect of strong colored noise, a noise-corrected clustered-sparse channel estimation (NC-CSCE) algorithm was proposed to improve the estimation accuracy. Numerical simulations and lake trials are conducted to verify the effectiveness of the algorithms. Results show that the proposed algorithms achieve higher channel estimation accuracy and lower bit error rate (BER). Full article
(This article belongs to the Special Issue Underwater Acoustics Modelling and Control)
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11 pages, 3051 KiB  
Communication
Localization of Immersed Sources by Modified Convolutional Neural Network: Application to a Deep-Sea Experiment
by Xu Xiao, Wenbo Wang, Lin Su, Xinyi Guo, Li Ma and Qunyan Ren
Sensors 2021, 21(9), 3109; https://doi.org/10.3390/s21093109 - 29 Apr 2021
Cited by 3 | Viewed by 1915
Abstract
A modified convolutional neural network (CNN) is proposed to enhance the reliability of source ranging based on acoustic field data received by a vertical array. Compared to the traditional method, the output layer is modified by outputting Gauss regression sequences, expressed using a [...] Read more.
A modified convolutional neural network (CNN) is proposed to enhance the reliability of source ranging based on acoustic field data received by a vertical array. Compared to the traditional method, the output layer is modified by outputting Gauss regression sequences, expressed using a Gaussian probability distribution form centered on the actual distance. The processed results of deep-sea experimental data confirmed that the ranging performance of the CNN with a Gauss regression output was better than that using single regression and classification outputs. The mean relative error between the predicted distance and the actual value was ~2.77%, and the positioning accuracy with 10% and 5% error was 99.56% and 90.14%, respectively. Full article
(This article belongs to the Special Issue Underwater Acoustics Modelling and Control)
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