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


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.