DocumentCode :
1841608
Title :
MUSIC algorithm applied to Advanced EMI sensors data for UXO classification
Author :
Economou, Dimitris P. ; Shubitidze, Fridon ; Barrowes, Benjamin ; Uzunoglu, Nikolaos K.
Author_Institution :
Microwave & Fiber Opt. Lab., Nat. Tech. Univ. of Athens, Athens, Greece
fYear :
2011
fDate :
12-16 Sept. 2011
Firstpage :
1160
Lastpage :
1163
Abstract :
The multiple signal classification (MUSIC) algorithm, that utilizes next generation electromagnetic induction (EMI) sensor, multi static response (MRS) data matrix´s eigenvector´s and eigenvalues, is employed for estimating number of subsurface metallic targets and pinpointing their location. The method divides MRS matrix data eigenvectors into two groups: the noise and signal subspaces. It projects the estimated EM signal into the noise subspace and utilizes the fact that the modeled magnetic field for each actual source location is orthogonal to the noise subspace. Data are presented for demonstrating the effectiveness of the method.
Keywords :
eigenvalues and eigenfunctions; electromagnetic induction; electromagnetic interference; matrix algebra; signal classification; MRS matrix data eigenvectors; MUSIC algorithm; UXO classification; advanced EMI sensors data; eigenvalues; magnetic field; multiple signal classification algorithm; multistatic response data matrix eigenvector; next generation electromagnetic induction sensor; subsurface metallic targets; unexploded ordnance; Arrays; Educational institutions; Eigenvalues and eigenfunctions; Electromagnetic interference; Multiple signal classification; Noise; Sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electromagnetics in Advanced Applications (ICEAA), 2011 International Conference on
Conference_Location :
Torino
Print_ISBN :
978-1-61284-976-8
Type :
conf
DOI :
10.1109/ICEAA.2011.6046514
Filename :
6046514
Link To Document :
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