Sonar discrimination of cylinders from different angles using neural networks

Author

Andersen, Lars Nonboe ; Au, Whitlow ; Larsen, Jan ; Hansen, Lars Kai

Author_Institution

Dept. of Math. Modelling, Tech. Univ., Lyngby, Denmark

Volume

2

fYear

1999

fDate

15-19 Mar 1999

Firstpage

1121

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

Keywords

feature extraction; hearing; neural nets; signal classification; sonar signal processing; underwater sound; angles; artificial neural networks; auditory model; cylinders; feature classification; feature extraction; neural networks; real data collection; simulated auditory filters; simulated dolphin clicks; sonar discrimination; underwater object discrimination system; Acoustic transducers; Biological system modeling; Computational biology; Dolphins; Filters; Gold; Mathematical model; Neural networks; Sonar; World Wide Web;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.759941

Filename

759941