Object detection and classification with a CTFM ultrasonic sensor

Recognising objects using sonar presents a significant research problem, especially when echo information for feature extraction is scarce. Blind people, however, have shown an amazing ability to identify such objects using an ultrasonic mobility aid. For example a blind man named Fred Gissoni was able to recognise a table and chair in a restaurant in order to find a place to eat. Bats have also demonstrated an amazing capacity to navigate in dark caves using ultrasonic echolocation. Given these remarkable feats, there must be more information in the signal of an echo than previously thought. If these features could be identified a more robust approach to recognising objects using sonar could be developed. This research attempts to address this issue using a framework based on Mahalanobis distance. As a particular example the echoes of a table and chair are studied.