Me. Zakharia et P. Chevret, Neural network approach for inverting velocity dispersion; application to sediment and to sonar target characterization, INVERSE PR, 16(6), 2000, pp. 1693-1708
A novel inversion method based on a neural network is presented. The parame
ter used for the inversion is the velocity dispersion of surface acoustic w
aves. The velocity law is computed using time-frequency representation (Wig
ner-Ville), which is a highly relevant tool for multi-component dispersive
signal analysis. The same inversion method has been applied to two physical
cases: inversion of geoacoustical parameters of seabeds and characterizati
on of sonar target properties. The method possesses high accuracy performan
ce (error less than a few per cent) in both cases on either simulated or ex
perimental data. The a priori information used for inversion is very poor a
nd limited to the physical description of the direct problem.