Fast Calculation of Underwater Acoustic Horizontal Range: A Guarantee for B5G Ocean Mobile Networks

被引:7
作者
Zhang, Tongwei [1 ]
Han, Guangjie [2 ]
Yan, Lei [3 ,4 ]
Peng, Yan [5 ]
机构
[1] Natl Deep Sea Ctr, Qingdao 266237, Peoples R China
[2] Hohai Univ, Dept Informat & Commun Syst, Changzhou 213022, Peoples R China
[3] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066044, Hebei, Peoples R China
[4] Chinese Acad Sci, Inst Acoust, State Key Lab Acoust, Beijing 100190, Peoples R China
[5] Shanghai Univ, Res Inst USV Engn, Shanghai 200000, Peoples R China
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2021年 / 8卷 / 04期
基金
中国国家自然科学基金;
关键词
Ocean mobile network; horizontal range; underwater acoustic; fast calculation; B5G; NAVIGATION; LOCALIZATION;
D O I
10.1109/TNSE.2020.3025571
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Autonomous underwater vehicle based mobile networks (AUV-MNs) are utilized in a wide range of marine applications and are likely to play a key role in the implementation of beyond 5G mobile space, air, ground, and sea networks. Communication technology and positioning technology are two key technologies for AUV-MNs, both of which are dependent on the accurate measurement of the underwater acoustic range. Furthermore, with the development of artificial intelligence, the rapid and accurate calculation of underwater acoustic range becomes more important, which affects the decision-making performance of AUV-MNs. In this paper, we propose a fast calculation method of the underwater acoustic horizontal range to guarantee a low-cost, long-endurance AUV-MN (l(2)-AUV-MN-2.0). Using this fast calculation method, we can obtain an accurate horizontal range for the AUV-MNs in a simple manner, thus ensuring the performance of the AUV-MNs. We verify the feasibility and the robustness of the proposed method via simulations. Furthermore, this fast calculation method can be used in other types of ocean networks or systems, such as leader-follower based multi-AUVs collaborative operation networks, and underwater cellular-type networks.
引用
收藏
页码:2922 / 2933
页数:12
相关论文
共 36 条
  • [21] GAUSSIAN-BEAM TRACING FOR COMPUTING OCEAN ACOUSTIC FIELDS
    PORTER, MB
    BUCKER, HP
    [J]. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 1987, 82 (04) : 1349 - 1359
  • [22] Multi-Tier Drone Architecture for 5G/B5G Cellular Networks: Challenges, Trends, and Prospects
    Sekander, Silvia
    Tabassum, Hina
    Hossain, Ekram
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (03) : 104 - 111
  • [23] Design and Capacity Analysis of Cellular-Type Underwater Acoustic Networks
    Stojanovic, Milica
    [J]. IEEE JOURNAL OF OCEANIC ENGINEERING, 2008, 33 (02) : 171 - 181
  • [24] Underwater Acoustic Communication Channels: Propagation Models and Statistical Characterization
    Stojanovic, Milica
    Preisig, James
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2009, 47 (01) : 84 - 89
  • [25] Localization and Data Collection in AUV-Aided Underwater Sensor Networks: Challenges and Opportunities
    Su, Ruoyu
    Zhang, Dengyin
    Li, Cheng
    Gong, Zijun
    Venkatesan, R.
    Jiang, Fan
    [J]. IEEE NETWORK, 2019, 33 (06): : 86 - 93
  • [26] Reinforcement Learning-Based Adaptive Modulation and Coding for Efficient Underwater Communications
    Su, Wei
    Lin, Jiamin
    Chen, Keyu
    Xiao, Liang
    En, Cheng
    [J]. IEEE ACCESS, 2019, 7 (67539-67550) : 67539 - 67550
  • [27] Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics
    Yuan, Chengzhi
    Licht, Stephen
    He, Haibo
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2018, 48 (10) : 2920 - 2934
  • [28] Future Trends in Marine Robotics
    Zhang, Fumin
    Marani, Giacomo
    Smith, Ryan N.
    Choi, Hyun Taek
    [J]. IEEE ROBOTICS & AUTOMATION MAGAZINE, 2015, 22 (01) : 14 - +
  • [29] [张居成 Zhang Jucheng], 2013, [哈尔滨工程大学学报, Journal of Harbin Engineering University], V34, P1497
  • [30] Low-Cost, Long-Endurance Cooperative Navigation Based on "Light" Marine Equipment in Deep Sea
    Zhang, Tongwei
    Yan, Lei
    Han, Guangjie
    Guizani, Nadra
    Liu, Jun
    [J]. IEEE NETWORK, 2021, 35 (02): : 222 - 228