MUSIC algorithm for location searching of dielectric anomalies from S-parameters using microwave imaging

Motivated by the biomedical engineering used in early-stage breast cancer detection, we investigated the use of MUltiple SIgnal Classification (MUSIC) algorithm for location searching of small anomalies using S-parameters. We considered the application of MUSIC to functional imaging where a small nu...

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Bibliographic Details
Published in:Journal of computational physics 2017-11, Vol.348, p.259-270
Main Authors: Park, Won-Kwang, Kim, Hwa Pyung, Lee, Kwang-Jae, Son, Seong-Ho
Format: Article
Language:English
Subjects:
Algorithms
Anomalies
Approximation
Bessel function
Biomedical engineering
Born approximation
Computational physics
Computer simulation
Dielectrics
Dipole antennas
Discriminant analysis
Experimental results
Microwave imaging
Multi-Static Response (MSR) matrix
MUltiple SIgnal Classification (MUSIC)
Parameters
S-parameters
Searching
Signal classification
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Summary:Motivated by the biomedical engineering used in early-stage breast cancer detection, we investigated the use of MUltiple SIgnal Classification (MUSIC) algorithm for location searching of small anomalies using S-parameters. We considered the application of MUSIC to functional imaging where a small number of dipole antennas are used. Our approach is based on the application of Born approximation or physical factorization. We analyzed cases in which the anomaly is respectively small and large in relation to the wavelength, and the structure of the left-singular vectors is linked to the nonzero singular values of a Multi-Static Response (MSR) matrix whose elements are the S-parameters. Using simulations, we demonstrated the strengths and weaknesses of the MUSIC algorithm in detecting both small and extended anomalies.
ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2017.07.035