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Vector-Sensor MUSIC for Polarized Seismic Sources Localization


This paper addresses the problem of high-resolution polarized source detection and introduces a new eigenstructure-based algorithm that yields direction of arrival (DOA) and polarization estimates using a vector-sensor (or multicomponent-sensor) array. This method is based on separation of the observation space into signal and noise subspaces using fourth-order tensor decomposition. In geophysics, in particular for reservoir acquisition and monitoring, a set of-multicomponent sensors is laid on the ground with constant distance between them. Such a data acquisition scheme has intrinsically three modes: time, distance, and components. The proposed method needs multilinear algebra in order to preserve data structure and avoid reorganization. The data is thus stored in tridimensional arrays rather than matrices. Higher-order eigenvalue decomposition (HOEVD) for fourth-order tensors is considered to achieve subspaces estimation and to compute the eigenelements. We propose a tensorial version of the MUSIC algorithm for a vector-sensor array allowing a joint estimation of DOA and signal polarization estimation. Performances of the proposed algorithm are evaluated.

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Correspondence to Sebastian Miron.

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Miron, S., Le Bihan, N. & Mars, J.I. Vector-Sensor MUSIC for Polarized Seismic Sources Localization. EURASIP J. Adv. Signal Process. 2005, 280527 (2005).

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Keywords and phrases

  • vector-sensor array
  • vector MUSIC
  • interspectral tensor
  • higher-order eigenvalue decomposition for 4th-order tensors