Characterization of sonar target data using Gabor wavelet features

Ananya Sen Gupta; Daniel Schupp

doi:10.1109/ACSSC.2015.7421444

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Conference proceeding

Characterization of sonar target data using Gabor wavelet features

Ananya Sen Gupta and Daniel Schupp

2015 49th Asilomar Conference on Signals, Systems and Computers, Vol.2016-, pp.1723-1726

11/2015

DOI: 10.1109/ACSSC.2015.7421444

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Abstract

We present a method of characterization of active sonar target response that makes use of physics-driven Gabor dictionaries. Key innovation is the combination of the useful characteristics of the Gabor wavelet (time/frequency localization) with an empirical approach to dictionary selection for underwater acoustics. We demonstrate over experimental field data that these features are both visually distinct and ideal for separation and classification via support vector machine.

Dictionaries

Gabor filters

Kernel

Robustness

Sonar detection

Supervised learning

Support vector machines

System identification

Underwater acoustics

Wavelet transforms

Details

Title: Subtitle: Characterization of sonar target data using Gabor wavelet features
Creators: Ananya Sen Gupta - University of Iowa
Daniel Schupp - University of Iowa
Resource Type: Conference proceeding
Publication Details: 2015 49th Asilomar Conference on Signals, Systems and Computers, Vol.2016-, pp.1723-1726
Publisher: IEEE
DOI: 10.1109/ACSSC.2015.7421444
ISSN: 1058-6393
eISSN: 2576-2303
Language: English
Date published: 11/2015
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197549802771

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