Document Type

Thesis

Date of Degree

Spring 2016

Degree Name

MS (Master of Science)

Degree In

Electrical and Computer Engineering

First Advisor

Ananya Sen Gupta

Abstract

The problem of characterization of active sonar target response has important applications in many fields, including the currently cost-prohibitive recovery of unexploded ordinance on the ocean floor. We present a method for recognizing these objects using a multidisciplinary approach that fuses machine learning, signal processing, and feature engineering. In short, by taking inspiration from other fields, we solve the problem of object recognition in shallow water in an inexpensive way. These techniques add to the body of explored knowledge in the field of active sonar processing and address real-world problems in the process.

Public Abstract

The problem of characterization of active sonar target response has important applications in many fields, including the currently cost-prohibitive recovery of unexploded ordinance on the ocean floor. We present a method for recognizing these objects using a multidisciplinary approach that fuses machine learning, signal processing, and feature engineering. In short, by taking inspiration from other fields, we solve the problem of object recognition in shallow water in an inexpensive way. These techniques add to the body of explored knowledge in the field of active sonar processing and address real-world problems in the process.

Keywords

publicabstract, Acoustic physics, Gabor wavelets, Machine learning

Pages

x, 92 pages

Bibliography

Includes bibliographical references (pages 86-92).

Copyright

Copyright 2016 Daniel Schupp-Omid

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