WIT Press


Target Classification With Artificial Neural Networks Using Ultrasonic Phased Arrays

Price

Free (open access)

Paper DOI

10.2495/AIENG930551

Volume

1

Pages

14

Published

1993

Size

1,200 kb

Author(s)

P.D. Smith, D.R. Bull & C. Wykes

Abstract

Target classification with artificial neural networks using ultrasonic phased arrays P.D. Smith," D.R. Bull" & C. Wykes& o Department of Electrical Engineering, University * Department of Manufacturing Engineering and Operations Management, University of Nottingham, University Park, Nottingham NG7 ABSTRACT 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 INTRODUCTION Ultrasonic transducers are commonly used, often in conjunction with other sensors, to provide a

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