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Underwater Perception and Sensing with Robotic Sensors and Networks
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Underwater Perception and Sensing with Robotic Sensors and Networks

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 9326

Special Issue Editors

Dr. Xuebo Zhang

E-Mail Website
Guest Editor
College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
Interests: sonar imaging; synthetic aperture sonar; synthetic aperture radar; image resolution; radar imaging; signal reconstruction; signal sampling
Special Issues, Collections and Topics in MDPI journals
Dr. Haixin Sun

E-Mail Website
Guest Editor
Deportment of Information and Communication Engineering, Xiamen University, 422 Siming South Road, Xiamen 361005, China
Interests: digital communications; wireless communications; modern signal processing; underwater acoustic communication
Special Issues, Collections and Topics in MDPI journals
Dr. Stanisław Hożyń

E-Mail Website
Guest Editor
Faculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, Poland
Interests: computer vision; machine learning; automation and control systems; underwater vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Underwater robotics such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) have become useful tools for many maritime applications. Underwater-robotics-based sensors and networks are drawing great attention due to their flexibility and easy deployment to significantly improve the perception area compared to traditional fixed sensors and networks. Mobile sensors and networks are often limited by the power supply and constrained communication resources. The performance of underwater perception and sensing is often affected by the robotics’ stability. With the development of robotic sensor technology, communication technology, automatic control technology, multisensor fusion technology, artificial intelligence, machine learning, and so on, underwater perception and sensing based on robotic sensors and networks have reached a new stage of development with new theories, methods, and technologies.

This Special Issue will focus on the use of robotic sensors and networks to address underwater perception and sensing. This issue is seeking original research papers on all aspects of robotic sensors, networks, and underwater perception and sensing, including but not limited to: computational fluid dynamics; ship hydrodynamics; underwater robotic sensor and network deployment; ocean environment perception; ocean acoustic tomography; monitoring of underwater acoustic fields; underwater navigation; localization, tracking, and detection; seafloor mapping; sub-bottom profiling; sonar technology; and applications of machine learning and artificial intelligence in underwater perception and sensing.

Dr. Xuebo Zhang
Dr. Haixin Sun
Dr. Stanisław Hożyń
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. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly 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

  • perception
  • sensing
  • robotics
  • sensor
  • network

Published Papers (5 papers)

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Research

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23 pages, 9874 KiB  
Article
A Subaperture Motion Compensation Algorithm for Wide-Beam, Multiple-Receiver SAS Systems
by Jiafeng Zhang, Guangli Cheng, Jinsong Tang, Haoran Wu and Zhen Tian
J. Mar. Sci. Eng. 2023, 11(8), 1627; https://doi.org/10.3390/jmse11081627 - 20 Aug 2023
Viewed by 840
Abstract
Uncompensated motion errors can seriously affect the imaging quality of synthetic aperture sonars (SASs). In the existing line-by-line motion compensation (MOCO) algorithms for wide-beam multiple-receiver SAS systems, the approximate form of the range history error usually introduces a significant approximation error, and the [...] Read more.
Uncompensated motion errors can seriously affect the imaging quality of synthetic aperture sonars (SASs). In the existing line-by-line motion compensation (MOCO) algorithms for wide-beam multiple-receiver SAS systems, the approximate form of the range history error usually introduces a significant approximation error, and the residual two-dimensional (2D) range cell migration (RCM) caused by aperture-dependent motion errors is not corrected, resulting in the severe defocus of the image. In this paper, in the presence of translational and rotational errors in a multiple-receiver SAS system, the exact range history error concerning the five-degree-of-freedom (DOF) motion errors of the sway, heave, yaw, pitch, and roll under the non-stop-hop-stop case is derived. Based on this, a two-stage subaperture MOCO algorithm for wide-beam multiple-receiver SAS systems is proposed. We decompose the range history error into the beam-center term (BCT) and the residual spatial-variant term (RSVT) to compensate successively. In the first stage, the time delay and phase error caused by the BCT are compensated receiver-by-receiver through interpolation and phase multiplication in the azimuth-time domain. In the second stage, the data of a single pulse are regarded as a subaperture, and the RSVT is compensated in the subaperture range-Doppler (RD) domain. We divide the range into several blocks to correct RCM caused by the RSVT in the subaperture RD domain, and the phase error caused by the RSVT is compensated by phase multiplication. After compensation, the wide-beam RD algorithm is used for imaging. Simulated and real-data experiments verify the superiority and robustness of the proposed algorithm. Full article
(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)
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17 pages, 3292 KiB  
Article
A Method for Inverting Shallow Sea Acoustic Parameters Based on the Backward Feedback Neural Network Model
by Hanhao Zhu, Zhiqiang Cui, Jia Liu, Shenghui Jiang, Xu Liu and Jiahui Wang
J. Mar. Sci. Eng. 2023, 11(7), 1340; https://doi.org/10.3390/jmse11071340 - 30 Jun 2023
Cited by 4 | Viewed by 957
Abstract
In response to the drawbacks of low efficiency, cumbersome calculation, and easy-to-fall local optimal solutions in existing shallow water acoustic parameters inversion research, this paper proposes a shallow water acoustic parameters inversion method based on a feedback (BP) neural network model. Firstly, the [...] Read more.
In response to the drawbacks of low efficiency, cumbersome calculation, and easy-to-fall local optimal solutions in existing shallow water acoustic parameters inversion research, this paper proposes a shallow water acoustic parameters inversion method based on a feedback (BP) neural network model. Firstly, the theoretically predicted values of the shallow water sound pressure field are obtained through the fast field method (FFM). Secondly, a relationship model between the predicted sound pressure field and the inversion of ground sound parameter values is established based on the BP neural network model. Finally, the measured sound pressure field data are brought into the neural network model to obtain the inversion results. The application results of the method indicate that, compared to the classical simulated annealing (SA) algorithm, the BP neural network model converts the data-matching process of the optimization algorithm into the construction of a relationship model between the input data and the desired parameters, avoiding repeated matching and optimization processes. Therefore, it can directly, accurately, and efficiently output the inversion results. Under the premise of setting the same accuracy, the iteration number of the BP neural network model is reduced to 2% of the SA algorithm, cutting the calculation time to 30% of the SA algorithm. It has broad application prospects in shallow sea acoustic parameters inversion algorithms. Full article
(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)
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14 pages, 865 KiB  
Article
Designing Protograph LDPC Codes for Differential Chaotic Bit-Interleaved Coded Modulation System for Underwater Acoustic Communications
by Zhiping Xu, Qiwang Chen, Yang Li, Guofa Cai, Lixiong Lin, Jiachun Zheng and Yanglong Sun
J. Mar. Sci. Eng. 2023, 11(5), 914; https://doi.org/10.3390/jmse11050914 - 24 Apr 2023
Viewed by 1268
Abstract
Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph [...] Read more.
Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph low-density parity-check (P-LDPC) code design framework for the differential chaotic bit-interleaved coded modulation (DC-BICM) system for UWA communication is proposed. This design framework, considering the requirements of short codes in UWA communications, integrates the DC-BICM system, UWA channel and the differential evolutionary code searching algorithm. Through this design framework, the optimized short P-LDPC code can be obtained. Simulation results show that the DC-BICM system with the proposed P-LDPC code can obtain more than 0.48 dB coding gain and reduce 32.6%~69.5% of the average number of iterations compared with the counterparts. Moreover, the reconstructed underwater image with the proposed P-LDPC code is clearest with the highest peak-signal-noise ratio value when compared with counterparts. Full article
(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)
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14 pages, 2087 KiB  
Article
An OFDM-Based Frequency Domain Equalization Algorithm for Underwater Acoustic Communication with a High Channel Utilization Rate
by Chengxu Feng, Yasong Luo, Jianqiang Zhang and Houpu Li
J. Mar. Sci. Eng. 2023, 11(2), 415; https://doi.org/10.3390/jmse11020415 - 14 Feb 2023
Cited by 1 | Viewed by 1983
Abstract
The underwater acoustic communication technique for high-speed and highly reliable information transmission in the ocean has been one of the popular research focuses facing the fast-growing information technology sector and the accelerating development of ocean resources. In order to achieve a high information [...] Read more.
The underwater acoustic communication technique for high-speed and highly reliable information transmission in the ocean has been one of the popular research focuses facing the fast-growing information technology sector and the accelerating development of ocean resources. In order to achieve a high information transmission rate with limited underwater acoustic channel bandwidth, researchers have paid much attention to the underwater acoustic communication technique based on orthogonal frequency division multiplexing (OFDM). A traditional OFDM-based frequency domain equalization algorithm relies on cyclic prefixes for the effective resistance to the multipath effect of an underwater acoustic channel. However, a redundant cyclic prefix may lead to a severe waste of energy and bandwidth in the underwater acoustic system if it is too long. The high utilization rate of OFDM signal channel will not be practically achieved in this case. Based on the limitations of the existing frequency domain equalization algorithm, this paper studied the influence of the multipath effect on the OFDM signal transmission. Subsequently, the principles of the OFDM-based frequency domain equalization were further explored for an improved structural model design of the communication system. On this basis, a novel frequency domain adaptive equalization algorithm was put forward. In addition, the proposed algorithm was optimized to address the problem of increased computation. The simulation results proved that the novel frequency domain equalization algorithm delivers a better symbol error ratio than the existing algorithm, and the compensation for the multipath effect through frequency selective fading. The proposed algorithm can realize the information transmission at a low symbol error ratio when fewer cyclic prefixes are used, so that it takes up a lower number of channels with cyclic prefixes in the OFDM communication system. Full article
(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)
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Review

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45 pages, 46634 KiB  
Review
A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems
by Naveed Ur Rehman Junejo, Mariyam Sattar, Saifullah Adnan, Haixin Sun, Abuzar B. M. Adam, Ahmad Hassan and Hamada Esmaiel
J. Mar. Sci. Eng. 2023, 11(4), 885; https://doi.org/10.3390/jmse11040885 - 21 Apr 2023
Cited by 5 | Viewed by 3186
Abstract
In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, [...] Read more.
In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits. Full article
(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)
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