Overview and Classification of Some Regularization Techniques for the Gauss-Newton Inversion Method Applied to Inverse Scattering Problems

Mojabi, Puyan; LoVetri, Joe

doi:10.1109/tap.2009.2027161

Cited by 118 publications

(59 citation statements)

References 42 publications

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“…Accordingly, the imaging problem consists of the solution (1) for γ(·). As is well known, this inversion is an ill-posed problem that must be handled with care through a regularized inversion scheme [18], [19]; here, we adopt a TSVD scheme [18].…”

Section: Tsvd Inverse Scattering Algorithmmentioning

confidence: 99%

A Novel CS-TSVD Strategy to Perform Data Reduction in Linear Inverse Scattering Problems

Solimene¹,

Ahmad

Soldovieri³

2012

IEEE Geosci. Remote Sensing Lett.

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High-resolution radar imaging systems employ wideband signals and large array apertures, resulting in the generation of large amounts of data. This renders both data acquisition and processing challenging. In this letter, we propose a hybrid approach for a stepped-frequency imaging radar system, which is based on the compressive sensing and novel concepts of microwave tomography, to establish a reduced-redundancy spatial and frequency measurement configuration. The proposed approach provides clear advantages in terms of measurement time and algorithm complexity while maintaining the quality of the scene reconstructions. Laboratory experiments are used to validate the hybrid strategy.Index Terms-Inverse scattering, microwave tomography, sparse reconstructions, through-the-wall imaging.

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Section: Tsvd Inverse Scattering Algorithmmentioning

confidence: 99%

A Novel CS-TSVD Strategy to Perform Data Reduction in Linear Inverse Scattering Problems

Solimene¹,

Ahmad

Soldovieri³

2012

IEEE Geosci. Remote Sensing Lett.

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“…The food sources selected by the onlooker bees are further improved by using (13). If a food source is not improved after a predefined number of iterations K lim (food source limit), that is,…”

Section: Artificial Bee Colonymentioning

confidence: 99%

“…In particular, two main classes of algorithms can be identified. Deterministic [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] and stochastic strategies [22][23][24][25][26][27][28][29][30][31][32][33]. Deterministic methods are usually fast and, when converge, they produce high quality reconstructions.…”

Section: Introductionmentioning

confidence: 99%

Swarm Optimization Methods in Microwave Imaging

Randazzo

2012

International Journal of Microwave Science and Technology

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Swarm intelligence denotes a class of new stochastic algorithms inspired by the collective social behavior of natural entities (e.g., birds, ants, etc.). Such approaches have been proven to be quite effective in several applicative fields, ranging from intelligent routing to image processing. In the last years, they have also been successfully applied in electromagnetics, especially for antenna synthesis, component design, and microwave imaging. In this paper, the application of swarm optimization methods to microwave imaging is discussed, and some recent imaging approaches based on such methods are critically reviewed.

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“…By reviewing the state-of-the-art literature, several techniques have been successfully developed in the frequency domain under the assumption of monochromatic illuminations [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. Despite their success, such inversion methods often present some limitations since only a reduced amount of information is actually retrievable from a single frequency measurement [30] and the exploitation of higher frequencies to enhance the spatial resolution [30,31] generally causes an increase of the complexity of the measurement system [31].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Scaling Forward-Backward Time-Stepping Method for microwave imaging

Moriyama

Oliveri

Salucci

et al. 2014

IEICE Electron. Express

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This paper is aimed at presenting a new time-domain imaging technique that combines the regularization properties of the Filtered FBTS method with an efficient information-acquisition strategy, namely the Iterative Multi-Scaling Approach (IMSA). The proposed time-domain approach is then validated by means of a set of preliminary numerical test cases aimed at pointing out its features and potentialities, as well.

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Overview and Classification of Some Regularization Techniques for the Gauss-Newton Inversion Method Applied to Inverse Scattering Problems

Cited by 118 publications

References 42 publications

A Novel CS-TSVD Strategy to Perform Data Reduction in Linear Inverse Scattering Problems

A Novel CS-TSVD Strategy to Perform Data Reduction in Linear Inverse Scattering Problems

Swarm Optimization Methods in Microwave Imaging

A Multi-Scaling Forward-Backward Time-Stepping Method for microwave imaging

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