DETECTION, RECONSTRUCTION, AND CHARACTERIZATION ALGORITHMS FROM NOISY DATA IN MULTISTATIC WAVE IMAGING

被引：6

作者：

Ammari, Habib ^{[1
]}

Garnier, Josselin ^{[2
,3
]}

Jugnon, Vincent ^{[4
]}

机构：

[1] Ecole Normale Super, Dept Math & Applicat, F-75005 Paris, France

[2] Univ Paris Diderot, Lab Probabilites & Modeles Aleatoires, F-75205 Paris 13, France

[3] Univ Paris Diderot, Lab Jacques Louis Lions, F-75205 Paris 13, France

[4] MIT, Dept Math, Cambridge, MA 02139 USA

来源：

DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S | 2015年 / 8卷 / 03期

关键词：

Multistatic wave imaging; noisy data; detection and reconstruction algorithms; random matrices; measurement noise; Helmholtz equation; SCATTERING-AMPLITUDE; INVERSE SCATTERING; NUMERICAL-METHODS; SMALL INCLUSIONS; CONDUCTIVITY; MATRIX;

D O I：

10.3934/dcdss.2015.8.389

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The detection, localization, and characterization of a collection of targets embedded in a medium is an important problem in multistatic wave imaging. The responses between each pair of source and receiver are collected and assembled in the form of a response matrix, known as the multi-static response matrix. When the data are corrupted by measurement or instrument noise, the structure of the response matrix is studied by using random matrix theory. It is shown how the targets can be efficiently detected, localized and characterized. Both the case of a collection of point reflectors in which the singular vectors have all the same form and the case of small-volume electromagnetic inclusions in which the singular vectors may have different forms depending on their magnetic or dielectric type are addressed.

引用

页码：389 / 417

页数：29

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