Noise-free fast sparse Bayesian learning method for robust multi-frequency underwater matched-field acoustic source localization

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics Pub Date : 2024-10-30 DOI:10.1016/j.apacoust.2024.110356

Qisen Wang , Hua Yu , Yankun Chen , Chao Dong , Jie Li , Fei Ji

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引用次数: 0

Abstract

In this paper, a matched-field processing (MFP) method based on sparse Bayesian learning (SBL) is proposed for robust multi-frequency underwater acoustic source localization. Firstly, a noise-free SBL framework is established by integrating the noise precision, which results in a heavy-tailed student-t posterior distribution potentially promoting the robustness for noise and environmental mismatch. Secondly, to enhance the computational efficiency, a modified fast SBL procedure is derived by sequentially maximizing the multi-frequency joint-sparsity marginal likelihood function. Finally, a new refined estimation strategy based on linear approximation is proposed to deal with the off-grid source localization problem. Simulations demonstrate that the proposed multi-frequency noise-free fast sparse Bayesian learning (MNFFSBL) algorithm not only has better performance than traditional MFP processors in scenarios of low SNR and modest environmental mismatch scenarios but also is much faster than the SBL method. The effectiveness of the proposed method is also validated by processing the data of the SWellEx-96 ocean acoustic experiment.

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用于稳健多频率水下匹配场声源定位的无噪声快速稀疏贝叶斯学习方法

本文提出了一种基于稀疏贝叶斯学习（SBL）的匹配场处理（MFP）方法，用于稳健的多频率水下声源定位。首先，通过整合噪声精度建立了无噪声 SBL 框架，从而得到重尾 student-t 后验分布，这可能会提高噪声和环境不匹配的鲁棒性。其次，为了提高计算效率，通过依次最大化多频联合稀疏边际似然函数，推导出一种改进的快速 SBL 程序。最后，提出了一种新的基于线性近似的精细估算策略，用于处理离网源定位问题。仿真表明，所提出的多频无噪声快速稀疏贝叶斯学习（MNFFSBL）算法不仅在低信噪比和适度环境失配情况下比传统的多频谱处理器性能更好，而且比 SBL 方法快得多。通过处理 SWellEx-96 海洋声学实验数据，也验证了所提方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Acoustics 物理-声学

CiteScore

7.40

自引率

11.80%

发文量

618

审稿时长

7.5 months

期刊介绍： Since its launch in 1968, Applied Acoustics has been publishing high quality research papers providing state-of-the-art coverage of research findings for engineers and scientists involved in applications of acoustics in the widest sense. Applied Acoustics looks not only at recent developments in the understanding of acoustics but also at ways of exploiting that understanding. The Journal aims to encourage the exchange of practical experience through publication and in so doing creates a fund of technological information that can be used for solving related problems. The presentation of information in graphical or tabular form is especially encouraged. If a report of a mathematical development is a necessary part of a paper it is important to ensure that it is there only as an integral part of a practical solution to a problem and is supported by data. Applied Acoustics encourages the exchange of practical experience in the following ways: • Complete Papers • Short Technical Notes • Review Articles; and thereby provides a wealth of technological information that can be used to solve related problems. Manuscripts that address all fields of applications of acoustics ranging from medicine and NDT to the environment and buildings are welcome.