Target classification with artificial neural networks using ultrasonic phased arrays
Bull, P. D. K. Smith, Catherine M. Wykes · Bristol Research (University of Bristol) · 1993
The problem of classifying objects from their ultrasonic signature for robotic applications is studied in this paper. The system developed utilises the spatial diversity of a four element linear array transducer to enhance classification performance. A signal pre-processing technique employing time domain envelope detection in combination with a multi-layer perceptron neural network has yielded classification success rates approaching 90% for previously unseen targets. This level of discrimination is not possible with a single sensor configuration