A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term. As the mean of the noise in the power spectrum domain is dependent on its variance in the time domain, the proposed method includes a variance estimation step, which allows more robust blind deconvolution. Validation of the method on both simulated and real data, and of its performance, are compared with two well-known methods from the literature: the deconvolution approach for the mapping of acoustic sources, and sound density modeling

Whistle source levels of free-ranging beluga whales in Saguenay-St. Lawrence marine park

International audienceWild beluga whistle source levels (SLs) are estimated from 52 three-dimensional (3D) localized calls using a 4-hydrophone array. The probability distribution functions of the root-mean-square (rms) SL in the time domain, and the peak, the strongest 3-dB, and 10-dB SLs from the spectrogram, were non-Gaussian. The average rms SL was 143.8 +- 6.7 dB re 1microPa at 1m. SL spectral metrics were, respectively, 145.8 +- 8 dB, 143.2 +-7.1 dB, and 138.5 +-6.9 dB re 1 microPa. 1microPa / Hz at 1m

Sparse Approximations for Quaternionic Signals

Abstract. In this paper, we introduce a new processing procedure for quaternionic signals through consideration of the well-known orthogonal matching pursuit (OMP), which provides sparse approximation. Due to quaternions noncommutativity, two quaternionic extensions are presented: the right-multiplication quaternionic OMP, that can be used to process right-multiplication linear combinations of quaternionic signals, and the left-multiplication quaternionic OMP, that can be used to process left-multiplication linear combinations. As validation, these quaternionic OMP are applied to simulated data. Deconvolution is carried out and presented here with a new spikegram that is designed for visualization of quaternionic coefficients, and finally these are compared to multivariate OMP

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 Nx-multicomponent sensors is laid on the ground with constant distance Δx 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

Propagation time sensitivity kernels obtained with double beam forming : towards a more robust tomography

La Tomographie Acoustique Océanique en milieu petit fond est un outil important pour la connaissance des milieux de propagation. Classiquement, celle-ci est réalisée en utilisant la théorie des rayons. Cependant, dans le cas de fréquences relativement basses, la théorie de rayons n'est plus valable. Des alternatives existent utilisant les 'Noyaux de Sensibilité', prenant en compte le contenu fréquentiel du signal. L'adaptation de ces Noyaux de Sensibilité du Temps de Propagation (NSTP) aux mesures réalisées via Double Formation de Voies (D-FV) est présentée dans ce papier. Les résultats montrent que les NSTP s'approchent de la théorie des rayons quand la D-FV est utilisée. Ceci valide ainsi l'utilisation de la théorie des rayons pour une tomographie utilisant des mesures issues de la D-FV