A MUSIC Algorithm for Locating Small Inclusions Buried in a Half-Space from the Scattering Amplitude at a Fixed Frequency

Ammari, Habib; Яковлева, Екатерина; Lesselier, Dominique

doi:10.1137/040610854

Cited by 180 publications

(162 citation statements)

References 19 publications

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“…Now, we end this section with the following example. Throughout some results in [4,23], it has been observed that MUSIC-type algorithm yields poorer results under the limited range of incident and observation directions. However, the proposed imaging algorithm is available for only a limited range of incident and observation directions.…”

Section: Numerical Examplesmentioning

confidence: 99%

Non-Iterative Imaging of Thin Electromagnetic Inclusions From Multi-Frequency Response Matrix

Park¹

2010

PIER

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Abstract-Although MUSIC (MUltiple SIgnal Classification)-type algorithm has shown feasibilities as a non-iterative imaging technique of thin penetrable electromagnetic inclusion from its far-field multistatic response (MSR) matrix, it induces a poor result whenever one tries to obtain such inclusion of both dielectric and magnetic contrast with respect to the embedding homogeneous space R 2 case. In this paper, we develop an improved non-iterative imaging algorithm based on the modeling of multi-frequency MSR matrix according to a rigorous asymptotic expansion of the scattering amplitude. Numerical examples exhibit that presented algorithm performs satisfactorily for single and multiple thin inclusions, even with a fair amount of random noise.

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Section: Numerical Examplesmentioning

confidence: 99%

Non-Iterative Imaging of Thin Electromagnetic Inclusions From Multi-Frequency Response Matrix

Park¹

2010

PIER

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“…Extending previous works in electromagnetics [2,3,5] to full 3D vector elasticity, we show how the eigenvalue structure of the MSR matrix can be employed within the framework of the MUSIC method in order to retrieve a 3D elastic inclusion.…”

Section: Introductionmentioning

confidence: 99%

“…Among all the direct reconstruction methods that have been developed during recent years, MUSIC-type algorithms seem to be particularly accurate and stable. In [2,3,5], we have designed robust numerical methods of MUSIC type for efficiently determining the locations and/or shapes of a collection of small acoustical and electromagnetic inclusions in both two-dimensional scalar scattering situations and 3D vector situations.…”

Section: Introductionmentioning

confidence: 99%

Direct Elastic Imaging of a Small Inclusion

Ammari¹,

Calmon²,

Яковлева³

2008

SIAM J. Imaging Sci.

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Abstract. In this paper we consider the problem of locating a small three-dimensional elastic inclusion, using arrays of elastic source transmitters and receivers. This procedure yields the multistatic response matrix that is characteristic of the elastic inclusion. We show how the eigenvalue structure of this matrix can be employed within the framework of a noniterative method of MUSIC (multiple signal classification) type in order to retrieve the elastic inclusion. We illustrate our reconstruction procedure with a variety of computational examples from synthetic, noiseless, and severely noisy data.

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“…Motivated from this, non-iterative techniques for retrieving the location of such inhomogeneities have been investigated. Those include the MUltiple SIgnal Classification (MUSIC) algorithm [5,6,7], the linear sampling method [8,9,10], and Kirchhoff and subspace migrations [11,12,13]. Although these techniques are confirmed to be fast, stable, and effective, they still require observations from a significant number of directions of the incident and scattered field or far-field data to obtain an acceptable result.…”

Section: Introductionmentioning

confidence: 99%

A Novel Study on Direct Sampling Method for Imaging Multiple Targets

Park¹

2017

dtetr

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Abstract. The Direct Sampling Method (DSM) is well known to be a fast, stable, and effective detection technique in inverse scattering problems, but its analysis is restricted to imaging of a single target. Motivated by this, we investigate the mathematical structure of DSM for imaging small multiple dielectric targets by establishing a relationship with the radii and permittivities of targets, and Bessel function of order zero. This structure explains why DSM can be applied to the imaging of multiple targets. Numerical results support our findings.

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A MUSIC Algorithm for Locating Small Inclusions Buried in a Half-Space from the Scattering Amplitude at a Fixed Frequency

Cited by 180 publications

References 19 publications

Non-Iterative Imaging of Thin Electromagnetic Inclusions From Multi-Frequency Response Matrix

Non-Iterative Imaging of Thin Electromagnetic Inclusions From Multi-Frequency Response Matrix

Direct Elastic Imaging of a Small Inclusion

A Novel Study on Direct Sampling Method for Imaging Multiple Targets

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