TITLE: Sonar Discrimination of Cylinders From Different Angles Using Neural Networks
AUTHORS: Lars Nonboe Andersen, Whitlow Au*, Jan Larsen and Lars Kai Hansen
Department of Mathematical Modelling, Building 321
Technical University of Denmark, DK-2800 Lyngby, Denmark
emails: jl,lna,mhm,lkhansen@imm.dtu.dk
www: http://eivind.imm.dtu.dk
*Marine Mammal Research Program,
Hawaii Institute of Marine Biology
University of Hawaii
P.O. 1106, Kailua, Hawaii, 96734, USA
ABSTRACT:
This paper describes an underwater object discrimination system applied to
recognize cylinders of various compositions from different angles. The
system is based on a new combination of simulated dolphin clicks,
simulated auditory filters and artificial neural networks. The model
demonstrates its potential on real data collected from four different
cylinders in an environment where the angles were controlled in order to
evaluate the models capabilities to recognize cylinders independent of
angles.
To be presented at ICASSP'99, Phoenix, Arizona, March 15-19, 1999.