Work

Autonomous feature discovery, representation and analysis for small SONAR targets using domain cognizant machine learning techniques

Year: 2025

Type: article

Abstract: This thesis uses machine learning to help develop an understanding of how the physics and geometry of different underwater objects affect how SONAR interacts with them. The key contributions are designing novel machine learning tools that use complex numbers, which incorporate phase information critical to physical interpretation of sonar targets.

Source: Iowa Research Online (The University of Iowa)

DOI: 10.25820/etd.007990

Author: Linhardt, Timothy J.

Language: English

Topic: Underwater Acoustics Research

Subfield: Oceanography

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7076268089

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