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.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-6514 |
| Date | 01 May 2016 |
| Creators | Schupp-Omid, Daniel |
| Contributors | Sen Gupta, Ananya |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2016 Daniel Schupp-Omid |
Page generated in 0.0018 seconds