The shape reconstruction of a strong large scattering object made up of elementary shapes and embedded within a large investigation domain is dealt with from the undersampled multifrequency backscattered field data. First, a migration algorithm is run that, despite aliasing, allows reducing the spatial region, where the scatterer can be located. Then, the overall shape is determined by identifying the elementary ones through a multiple signal classification algorithm. The approach is numerically tested for a 2-D geometry, and it proves to be robust against uncertainties on data.
A Strategy for Reconstructing Simple Shapes From Undersampled Backscattered Data
LEONE, Giovanni;SOLIMENE, Raffaele
2016
Abstract
The shape reconstruction of a strong large scattering object made up of elementary shapes and embedded within a large investigation domain is dealt with from the undersampled multifrequency backscattered field data. First, a migration algorithm is run that, despite aliasing, allows reducing the spatial region, where the scatterer can be located. Then, the overall shape is determined by identifying the elementary ones through a multiple signal classification algorithm. The approach is numerically tested for a 2-D geometry, and it proves to be robust against uncertainties on data.File in questo prodotto:
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