Modes Separation based on Compressive Sensing and Coordinate Transformation

Liang, Yuquan; Zhou, Shihong; Gong, Zhong‐Liang

doi:10.1109/ieeeconf38699.2020.9389192

Cited by 1 publication

(2 citation statements)

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“…Namely, one linear constraint exists between the elements of 𝑡 3 , 𝑡 3 only has k-2 independent elements, and others can be obtained through Eq. (20) and Eq. (21).…”

Section: B Solve Degeneracy Theorymentioning

confidence: 99%

See 1 more Smart Citation

Normal Mode Separation Method Based on the Consistency Constraint of the Horizontal Wavenumber

Gao,

Li,

Liu

et al. 2024

IEEE Access

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Normal mode separation and information extraction are popular topics in marine acoustics. The extraction of modal wavenumbers and modal depth functions using the data of a vertical line array is beneficial to various applications. In this paper, we systematically introduce a normal mode separation method based on the consistency restraint of the horizontal wavenumber, obtain the modal depth functions using the singular value decomposition (SVD) method, determine the vertical distribution of the horizontal wavenumber, and determine the SVD accuracy by the consistency of modal wavenumbers on the vertical direction. Moreover, this method can be used to determine the SVD accuracy without true depth functions. When the degeneracy problem leads to a poor SVD effect, the linear relation between the degenerate and true modes is obtained, and the minimum standard deviation of the vertical distribution of the modal wavenumbers is taken as the loss function, thus optimizing the SVD result and improving the accuracy of modal wavenumber estimation. The proposed method is validated using simulated data. In addition, the modes are successfully extracted from ambient noise.

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“…Namely, one linear constraint exists between the elements of 𝑡 3 , 𝑡 3 only has k-2 independent elements, and others can be obtained through Eq. (20) and Eq. (21).…”

Section: B Solve Degeneracy Theorymentioning

confidence: 99%

“…The environmental mismatch problem due to incomplete measurements is the biggest issue in practical applications. Several approaches have been proposed to address this problem, such as the data-derived method [9], [10], [11], [12], time-warping method [6], [13], [14], [15], [16], [17], and compressive sensing method [18], [19], [20].…”

Section: Introductionmentioning

confidence: 99%