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PANG Jie, GAO Bo, GAO Dazhi. Quantification method for uncertainty in deep-sea acoustic channels[J]. ACTA ACUSTICA, 2025, 50(3): 778-787. DOI: 10.12395/0371-0025.2024418
Citation: PANG Jie, GAO Bo, GAO Dazhi. Quantification method for uncertainty in deep-sea acoustic channels[J]. ACTA ACUSTICA, 2025, 50(3): 778-787. DOI: 10.12395/0371-0025.2024418

Quantification method for uncertainty in deep-sea acoustic channels

More Information
  • PACS: 
    • 43.30  (Underwater sound)
    • 43.60  (Acoustic signal processing)
    • 43.50  (Noise: its effects and control)
  • Received Date: December 30, 2024
  • Revised Date: January 26, 2025
  • This paper presents a method for quantifying uncertainty in deep-sea acoustic channels based on eigenvalue distributions and probabilistic distances. By analyzing the cross-spectral density matrix of received signals, the method classifies and quantifies both model uncertainty and channel uncertainty. Model uncertainty measures the differences between the acoustics observed in sea trials and the simulated sound fields, while channel uncertainty describes the deviation between the measured deep-sea acoustic channels and an idealized completely random channel. The Jensen-Shannon divergence and Wasserstein distance are used as primary metrics, and the random matrix theory is applied to analyze the eigenvalue distributions of deep-sea channels. Simulation results demonstrate that model uncertainty and channel uncertainty exhibit different sensitivities to variations in signal-to-noise ratio. The experimental results demonstrate that the statistical analysis of frequency-domain signal eigenvalues effectively mitigates the challenges posed by insufficient experimental data sampling, while validating the applicability of the proposed method in a specified experimental area of the South China Sea. Further analysis reveals that the deep-sea acoustic channel uncertainty reaches its minimum value in the proximity of 3 km from the sound source within this marine region.

  • [1]
    Rosenberg A P. A new rough surface parabolic equation program for computing low frequency acoustic forward scattering from the ocean surface. J. Acoust. Soc. Am, 1999; 105(1): 144−153 DOI: 10.1121/1.424626
    [2]
    Porter M B, Liu Y C. Finite-element ray tracing. In: Lee D, Schultz M H (eds). Theoretical and computational acoustics. Singapore: World Scientific, 1994: 947–956
    [3]
    Bucker H P. A simple 3-D Gaussian beam sound propagation model for shallow water. J. Acoust. Soc. Am., 1994; 95(5): 2437−2440 DOI: 10.1121/1.409853
    [4]
    Weinberg H, Keenan R E. Gaussian ray bundles for modeling high-frequency propagation loss under shallow-water conditions. J. Acoust. Soc. Am., 1996; 100(3): 1421−1431 DOI: 10.1121/1.415989
    [5]
    李整林, 余炎欣. 深海声学研究进展. 科学通报, 2022; 67(2): 125−134 DOI: 10.1360/TB-2021-0643
    [6]
    Qarabaqi P, Stojanovic M. Statistical characterization and computationally efficient modeling of a class of underwater acoustic communication channels. IEEE J. Oceanic Eng., 2013; 38(4): 701−717 DOI: 10.1109/JOE.2013.2278787
    [7]
    Pranitha B, Anjaneyulu L. Performance evaluation of a MIMO based underwater communication system under fading conditions. Eng. Technol. Appl. Sci. Res., 2019; 9(6): 4886−4892 DOI: 10.48084/etasr.3132
    [8]
    Cover T M. Elements of information theory. New York: John Wiley & Sons, 1999
    [9]
    Proakis J G, Salehi M. Digital communications. New York: McGraw-Hill, 2008
    [10]
    Tulino A R, Biglieri E. Random matrix theory and wireless communications. Piscataway, NJ: IEEE Press, 2004
    [11]
    Ali W, Lermusiaux P F J. Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part I: Theory and schemes. J. Acoust. Soc. Am., 2024; 155(1): 640−655 DOI: 10.1121/10.0024466
    [12]
    Ali W, Lermusiaux P F J. Dynamically orthogonal narrow-angle parabolic equations for stochastic underwater sound propagation. Part II: Applications. J. Acoust. Soc. Am., 2024; 155(1): 656−672 DOI: 10.1121/10.0024474
    [13]
    Khazaie S, Wang X, Komatitsch D, et al. Uncertainty quantification for acoustic wave propagation in a shallow water environment. Wave Motion, 2019; 91: 102390 DOI: 10.1016/j.wavemoti.2019.102390
    [14]
    Lee B M, Johnson J R, Dowling D R. Predicting acoustic transmission loss uncertainty in ocean environments with neural networks. J. Marine Sci. Eng., 2022; 10(10): 1548 DOI: 10.3390/jmse10101548
    [15]
    Khurjekar I, Gerstoft P. Distribution-free prediction intervals with conformal prediction for acoustical estimation. J. Acoust. Soc. Am., 2024; 156(4): 2656−2667 DOI: 10.1121/10.0032452
    [16]
    Pang J, Gao B, Wang N. Asymptotic spectral distribution of a second-order progressive scattering channel. IEEE Signal Process. Lett., 2024; 31: 1404−1408 DOI: 10.1109/LSP.2024.3399666
    [17]
    Jensen F B, Kuperman W A, Porter M B, et al. Computational ocean acoustics. 2nd edition. New York: Springer, 2011
    [18]
    Marčenko V A, Pastur L A. Distribution of eigenvalues for some sets of random matrices. Math. USSR-Sbornik, 1967; 114(4): 507−536 DOI: 10.1070/SM1967v001n04ABEH001994
    [19]
    Arjovsky M, Chintala S, Bottou L. Wasserstein generative adversarial networks. The 34th International Conference on Machine Learning, Sydney, Australia, 2017
    [20]
    王景强. 海底底质声学原位测量技术和声学特性研究. 博士学位论文, 北京: 中国科学院研究生院, 2015
    [21]
    Porter M B. The BELLHOP manual and user’s guide: Preliminary draft. SACLANTCEN Report SR-443, 2011
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