Automatic Detectors for Underwater Soundscape Measurements
Access Status
Open access
Authors
Madhusudhana, Shyam Kumar
Date
2015Supervisor
Dr Christine Erbe
Assoc. Prof. Alexander Gavrilov
Type
Thesis
Award
PhD
Metadata
Show full item recordSchool
Department of Physics and Astronomy, Centre for Marine Science and Technology
Collection
Abstract
Environmental impact regulations require that marine industrial operators quantify their contribution to underwater noise scenes. Automation of such assessments becomes feasible with the successful categorisation of sounds into broader classes based on source types – biological, anthropogenic and physical. Previous approaches to passive acoustic monitoring have mostly been limited to a few specific sources of interest. In this study, source-independent signal detectors are developed and a framework is presented for the automatic categorisation of underwater sounds into the aforementioned classes.