Classification of acoustic backscatter using the generalized target description

A new feature for the classification of echoes of a transmitted signal based on the generalized target description is described, and a framework for adaptive classification using it is presented. The generalized target description is a parametric model for the target impulse response. The feature is an order parameter from this model, which can be computed empirically from the growth rate of power as a function of a scale for a certain wavelet transform of the echo. A set of acoustic backscatter data consisting of returns from a mine and a rock with a linear FM transmit signal was analyzed. Parameters for the wavelet were computed from training sets so that this feature correctly distinguished 94% of the returns is test sets at 15 dB. The effectiveness of this feature as a classifier was found to degrade reasonably under increasing levels of synthetically generated reverberation noise. The simplest generalized target description model, a single order single center scatterer, was used. This model is not a realistic representation of the target impulse responses of either of the two objects, nevertheless it captured enough of the difference between the two to provide an effective classification tool.