Deconvolution for transient classification using fourth order statistics

Abstract

Considered are numerical experiments involving an exponentially damped harmonic source signature, and underwater acoustics Green's functions (GFs) representing bottom-limited propagation in a wave guide. It has been shown that the fourth order blind deconvolution functional proposed by Wiggins (1978) can be used to generate a class of signals from the propagation distorted signature such that one or more members of the class are "close" to the original signature. There are obvious applications to improving sonar target classification in the presence of multipath distortion. In this paper it is demonstrated that the algorithm based on the Cabrelli (1984) functional (D-norm) can be implemented in a similar fashion, and that it performs significantly better in the presence of additive noise than does the Wiggins V-norm.