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Abstract
Target recognition and classification applied to radar and sonar systems has become of great importance in recent years following the development of high range resolution systems that allow a much more detailed target sensing. Although a lot of research has been done on these topics, classification of targets under all weather and clutter conditions remains a key problem in many military applications and often not much data is available. Ultrasound measurements offer a relatively simple and inexpensive way to collect target data that can be used to exploit the performance of classifiers on scaled targets. In this thesis, classification of scaled radar target data collected at ultrasound frequencies is presented. Performance of various classifiers is assessed as a function of parameters, such as target features, SNR and angular perspectives.
