| dc.contributor.author | Shajahan, Najeem | |
| dc.date.accessioned | 2022-04-12T13:21:57Z | |
| dc.date.available | 2022-04-12T13:21:57Z | |
| dc.date.issued | 2022-04-12T13:21:57Z | |
| dc.identifier.uri | http://hdl.handle.net/10222/81527 | |
| dc.description | The spatial and temporal properties of ocean ambient noise are important factors to consider in the design of passive and active acoustic systems. The methods introduced in this thesis discuss the benefits of using two vertically-separated sensors in noise data analysis and passive acoustic monitoring. In chapter 2, a two-component noise model of coherence was developed, considering wind and shipping as major sources. A technique for source localization using vertical coherence was described in chapter 3. In chapter 4, a tool for visualizing the spatial variation in wind-generated noise coherence was introduced. These maps can be used to design the ideal spacing of multi-element vertical hydrophone arrays in the continental shelf and slope regions for signal detection optimization. Finally, in chapter 5, the theory of a three-component noise model, which can be used to identify the depth-dependence of various noise sources under two different local wind conditions was presented. These methods encourage the use of vertical pairs of hydrophones in acoustic monitoring of the ocean for soundscape studies and remote sensing. | en_US |
| dc.description.abstract | The spatial coherence of ambient noise can be used for noise-based inversion studies using appropriate coherence models. The main findings of this thesis are presented in four chapters. In chapter 2, using a two-component noise coherence model (wind and shipping), an inversion scheme is developed to determine the relative and absolute contribution of frequency-dependent ship noise to the total sound field. A simple model of vertical coherence for a broadband acoustic source is developed in chapter 3 to understand the characteristics of the sound field produced by ships. In the fourth chapter, a map of vertical noise coherence is generated to study the environmental dependence of vertical coherence at the mesoscale. Finally, in chapter 5, a three-component (wind, close-range shipping, and distant wind and shipping) depth-dependent noise coherence model is developed to identify and partition the noise field in deep water. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Ambient noise | en_US |
| dc.subject | Vertical coherence | en_US |
| dc.subject | source localization | en_US |
| dc.title | OCEAN SOUND FIELD CHARACTERIZATION USING PROCESSING TECHNIQUES BASED ON NOISE SPATIAL COHERENCE | en_US |
| dc.date.defence | 2022-03-04 | |
| dc.contributor.department | Department of Oceanography | en_US |
| dc.contributor.degree | Doctor of Philosophy | en_US |
| dc.contributor.external-examiner | Dr. Jennifer Miksis-Olds | en_US |
| dc.contributor.graduate-coordinator | Dr. Stephanie Kienast | en_US |
| dc.contributor.thesis-reader | Dr. Michael Dowd | en_US |
| dc.contributor.thesis-reader | Dr. Eric Oliver | en_US |
| dc.contributor.thesis-reader | Dr. Christopher Algar. | en_US |
| dc.contributor.thesis-supervisor | Dr. David Barclay | en_US |
| dc.contributor.ethics-approval | Not Applicable | en_US |
| dc.contributor.manuscripts | Yes | en_US |
| dc.contributor.copyright-release | Yes | en_US |
