DocumentCode
19550
Title
MUSIC Algorithms for Grid Diagnostics
Author
Solimene, Raffaele ; Leone, Giovanni
Author_Institution
Dipt. di Ing. dell´´Inf., Seconda Univ. di Napoli, Aversa, Italy
Volume
10
Issue
2
fYear
2013
fDate
Mar-13
Firstpage
226
Lastpage
230
Abstract
The problem of detecting and localizing missing scatterers (faults) inside a known grid of small cross-sectional perfect-electric-conducting cylinders is dealt with. The case of a TM scalar 2-D geometry is considered, and the Multiple Signal Classification (MUSIC) spectral estimation technique is employed. Two different scattering models are employed and compared. The first one aims at localizing present objects within a free-space background medium. The second one aims at detecting the faults and exploits the Green´s function of the full grid. The limitations of the first approach are pointed out and connected to the maximum dimension of the data space. Then, the second approach performs successfully when the fault number is lower than scattering objects.
Keywords
Green´s function methods; grid computing; signal classification; Green function; MUSIC algorithms; MUSIC spectral estimation technique; TM scalar 2D geometry; fault detection; fault localization; free-space background medium; grid diagnostics; missing scatterers; multiple signal classification; small cross-sectional perfect-electric-conducting cylinders; Green´s function methods; Inverse problems; Multiple signal classification; Noise; Optimized production technology; Scattering; Vectors; Grid diagnostics; Multiple Signal Classification (MUSIC) algorithm; microwave imaging; object localization;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2012.2198043
Filename
6221948
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