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基于张量演化的动态模态分解用于声源深度估计

Dynamic Mode Decomposition by Tensor Evolution for Source Depth

Wenqian Wu, Xiaohong Yang, Guangying Zheng, Lei Cheng, Peter Gerstoft

arXiv 2609.22266首次发表:更新:

发表机构

Polytechnic Institute, Zhejiang University; Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute; College of Information Science and Electronic Engineering, Zhejiang University; Acoustic Technology, Department of Electrical and Photonics Engineering, Technical University of Denmark(浙江大学工程师学院; 杭州应用声学研究所声纳技术重点实验室; 浙江大学信息与电子工程学院; 丹麦技术大学电气与光子工程系声学技术)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

针对低信噪比下深海近底垂直阵列浅源深度估计脆弱问题,提出基于张量演化的TEDS方法,利用动态模态分解和低秩Tucker分解分离特征与噪声,经傅里叶求和推断深度,实验证明其鲁棒性优于传统方法。

AI 中文摘要

利用深海近海底垂直阵列对浅海声源进行深度估计依赖于对深度敏感的干涉现象,该现象在宽带匹配波束强度处理(MBIP)中表现为频率-角度域内的振荡结构。针对低信噪比(低SNR)情况,MBIP中的非线性特征提取将阵列域噪声转化为特征域畸变,使得深度估计变得脆弱。为解决这一问题,我们受动态模态分解(DMD)启发,提出了一种基于张量演化的深度估计(TEDS)方法,该方法将一系列宽带MBIP表面解释为由时变自回归算子驱动的动态系统输出。该算子通过低秩Tucker分解表示,将相干特征模态及其时间模态与非相干噪声分离。通过对一个主导特征模态进行傅里叶求和来推断目标深度。深海数值实验表明,TEDS在低信噪比下提高了鲁棒性,始终优于匹配场处理(MFP)和宽带MBIP。

英文摘要

Depth estimation of shallow acoustic sources using a deep-ocean near-bottom vertical line array relies on depth-sensitive interference, which appears as an oscillatory structure in the frequency-angle domain in broadband matched beam-intensity processing (MBIP). For low-SNR, the nonlinear feature extraction in MBIP transforms array-domain noise into feature-domain distortions, making depth estimation fragile. Addressing this issue, we propose a tensor evolution-based depth estimation (TEDS) method inspired by dynamic mode decomposition (DMD), which interprets a sequence of broadband MBIP surfaces as the output of a dynamic system from a time-varying autoregressive operator. The operator is represented by a low-rank Tucker decomposition, which separates coherent feature modes and their temporal modes from incoherent noise. The target depth is inferred via Fourier summation applied to a dominant feature mode. Deep-ocean numerical experiments demonstrate that TEDS improves robustness at low-SNR, consistently outperforming matched field processing and broadband MBIP.

Comments13 pages, 11 figures, 4 tables. Accepted by Journal of the Acoustical Society of America

Journal refJ. Acoust. Soc. Am. 160, 2356-2369 (2026)

DOI:10.1121/10.0046532

论文原文

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