Feature extraction based on eigenvector analysis applied to the monostatic scattered field of a ribbed finite cylinder

Abstract

Feature extraction based on eigenvector analysis is applied to the monostatic response of a ribbed finite cylindrical shell with hemispherical end caps. The method, which is based on the Karhunen–Loeve expansion, is applied in the frequency domain to extract features for optimal representation of the data. An orthonormal set of eigenvectors that form a set of basis functions are computed by diagonalizing the correlation matrix. The expansion of the monostatic scattered field with the resultant set of basis functions is optimal because a small number of the functions is required to approximate the scattered field at each orientation of the scatterer. Such a representation reduces the dimensionality of the problem by more than an order of magnitude. The method is applied to two frequency ranges. In the first case, enhancements in target strength are present due to the phase matching of the elastic waves to the acoustic waves in the exterior fluid. In the second case, Bloch wave resonances are present due to the periodicity of the ribs. It is shown that as larger variations are present in target strength as a function of frequency, a larger number of eigenvectors are necessary to approximate the scattering response.