Multicomponent wave separation using HOSVD-Unimodal ICA subspace Method
International audienceIn this article, we use a three-mode model (polarization mode, distance mode, and temporal mode) to take into account the specific structure of signals that are recorded with these arrays, providing a data-structure-preserving processing. With the suggested model, we propose a multilinear decomposition named higher-order singular value decomposition and unimodal independent component analysis (HOSVD/unimodal ICA) to split the recorded three-mode data into two orthogonal subspaces: the signal and noise subspaces. This decomposition allows the separation and identification of polarized waves with infinite apparent horizontal propagation velocity. The HOSVD leads to a definition of a subspace method that is the counterpart of the well-known subspace method for matrices that is driven by singular value decomposition (SVD), a classic tool in monocomponent array processing
seismic waves, geophysical techniques, geophysical signal processing, singular value decomposition, independent component analysis, source separation, data acquisition, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], [SDE.MCG]Environmental Sciences/Global Changes, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Publisher: 'Society of Exploration Geophysicists'
DOI identifier: 10.1190/1.2335387
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