Title :
MUSIC Algorithms for Grid Diagnostics
Author :
Solimene, Raffaele ; Leone, Giovanni
Author_Institution :
Dipt. di Ing. dell´´Inf., Seconda Univ. di Napoli, Aversa, Italy
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;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2012.2198043
