Surface identification by acoustic reflection characteristics using delay spectrometry and artificial neural networks

The identification of surfaces using incident sound waves is associated with a variety of different applications including, sonar, seabed scanning and medical ultrasound imaging. The biologically innocuous nature, applicability, and simplicity involved in generation and measurement, makes sound inherently a more attractive agent for most applications. Time delay spectrometry can be employed as a way of isolating a desired reflected signal from other reflections dramatically increasing the signal to noise ratio of the receiver of a neural network based classification system. A surface classification system with the analysis of its performance will be introduced in this paper as a successful implementation of the proposed methodology.