Time-reversal multiple signal classification in case of noise: A phase-coherent approach

Asgedom, Endrias G.; Gelius, Leiv‐J.; Austeng, Andreas; Holm, Sverre; Tygel, Martin

doi:10.1121/1.3626526

Cited by 35 publications

(8 citation statements)

References 17 publications

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“…We recall that stability property is important for TR-MUSIC, and has been investigated by numerical means [26], [27] or using compressed-sensing based approaches [28]. Finally, a few numerical examples, for a 2-D geometry with scalar scattering, are presented to confirm our findings.…”

Section: Introductionsupporting

confidence: 57%

Noncolocated Time-Reversal MUSIC: High-SNR Distribution of Null Spectrum

Ciuonzo¹,

Rossi

2017

IEEE Signal Process. Lett.

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We derive the asymptotic distribution of the null spectrum of the well-known Multiple Signal Classification (MU-SIC) in its computational Time-Reversal (TR) form. The result pertains to a single-frequency non-colocated multistatic scenario and several TR-MUSIC variants are here investigated. The analysis builds upon the 1st-order perturbation of the singular value decomposition and allows a simple characterization of null-spectrum moments (up to the 2nd order). This enables a comparison in terms of spectrums stability. Finally, a numerical analysis is provided to confirm the theoretical findings.

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Section: Introductionsupporting

confidence: 57%

Noncolocated Time-Reversal MUSIC: High-SNR Distribution of Null Spectrum

Ciuonzo¹,

Rossi

2017

IEEE Signal Process. Lett.

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“…The pseudospectrum in equation 16 is expressed by a nil-space projection. Alternatively, that pseudospectrum can be constructed using its counterpart signal-space projection (Biondi and Kostov, 1989;Asgedom et al, 2011a). After spatial smoothing, the steered data window will contain essentially one aligned event in case of a true diffractor.…”

Section: Description Of Window-steered Musicmentioning

confidence: 99%

“…Time-reversal MUSIC can handle correlated sources but is sensitive to noise for some acquisition geometries . To make time-reversal MUSIC more robust, multifrequency versions have been developed (Asgedom et al, 2011a;Solimene et al, 2012). In this work, a windowed or steered type of classical MUSIC is used, with window being defined by the migration operator in use.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, much attention has been paid to the enhancement and separation of diffractions from reflection data for many imaging purposes. Several approaches have been proposed, among them the use of antistationary filtering (Moser and Howard, 2008), plane-wave destruction filters (Fomel et al, 2007), multifocusing (MF) (Berkovitch et al, 2009), or the common reflection surface (CRS) (Asgedom et al, 2011a(Asgedom et al, , 2011b(Asgedom et al, , 2012a(Asgedom et al, , 2012b stacking methods. Because the diffracted events are known to carry high-resolution information about the subsurface, their optimal use in imaging is an important topic.…”

Section: Introductionmentioning

confidence: 99%

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High-resolution imaging of diffractions — A window-steered MUSIC approach

et al. 2013

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Enhancement of diffractions and their use to resolve finescale details in a seismic image is increasingly important. Diffractions carry useful information about small-scale characteristics of the subsurface associated with features such as faults, pinch-outs, stratigraphic variations, and other geologic features linked to hydrocarbon reservoirs. Extracting the information content of diffractions and forming an image of the features they illuminate are not trivial tasks. The conventional approach relies on seismic migration, or modifications of seismic migration, and is thus limited by the Rayleigh criterion. The limited aperture and finite bandwidth make it difficult to extract all the potential information content. An alternative approach that overcomes such limitations is to turn to signal processing approaches, which extract information from the structure of the data with the aim of detecting and characterizing a finite number of desired events. Our interest is in diffractions, so we used a windowed or steered version of the MUltiple SIgnal Classification method. Use of this method allowed diffractions to be imaged at resolutions finer than the Rayleigh limit.

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“…[1][2][3][4][5][6][7][8][9][10] To improve ultrasound images, several methods to correct the phase aberration of transmitted ultrasound have been proposed. [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] The use of iteration has shown great promise in several studies. Reference 25 proposed a method to estimate the appropriate delay time by calculating the correlation of received signals between neighboring elements.…”

Section: Introductionmentioning

confidence: 99%

Phase aberration correction for focused ultrasound transmission by refraction compensation

Yasuda¹,

Yoshikawa²,

Tanaka³

2019

Jpn. J. Appl. Phys.

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Phase aberration of focused ultrasound by tissue structure causes focus degradation and reduces the quality of B-mode images. Refraction at the boundary between subcutaneous fat and muscle is one of the dominant factors behind such degradation. To correct this, we propose a refraction compensation method in which ultrasound is transmitted and received twice. The boundary shape between different tissues is detected by the first ultrasound transmission. Next, ultrasound rays from probe elements to the target are calculated taking refraction into account. Corrected delay times are calculated from the length of the rays and the sound velocity of the medium. Finally, ultrasound is transmitted a second time using the corrected delay time and a B-mode image is created. We evaluate the correction effect of the proposed method by numerical simulation and experiments with non-compensated and refraction-compensated cases of intensity distribution of the focused ultrasound. Results show that focus degradation is effectively corrected by the proposed method.

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Time-reversal multiple signal classification in case of noise: A phase-coherent approach

Cited by 35 publications

References 17 publications

Noncolocated Time-Reversal MUSIC: High-SNR Distribution of Null Spectrum

Noncolocated Time-Reversal MUSIC: High-SNR Distribution of Null Spectrum

High-resolution imaging of diffractions — A window-steered MUSIC approach

Phase aberration correction for focused ultrasound transmission by refraction compensation

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