Department Of Physical Oceanography, Cochin University Of Science And Technology  - Elizabeth Shani N. X.
Elizabeth Shani N. X.
Reg. No. 5285



Email  | Modelling of underwater ambient noise and light field

Phone | 9746779931


PhD Details

Joining Date | 21.07.2016

Supervising guide | Dr. R. Sajeev

Field of study | Oceanography

Title | Modeling of Underwater Ambient Noise Field



Modeling of Underwater Ambient Noise Field

The preferred energy used for underwater applications whether it is navigation, military, fishery, geological mapping or oceanographic sensors is sound, as electromagnetic waves attenuate faster in water. To detect any acoustic signal, the necessary condition is that its level should be sufficiently higher than the ambient noise level. However ambient noise varies with season location and frequency as seawater characteristics has both temporal and spatial variability. The noise level at a location depends mainly on the noise source characteristics, ocean sound speed structure, surface and bottom parameters. Depending on the type of application different frequency bands are used in acoustic systems, such as passive and active ASW sonars (with in 5 kHz), communication sonars (< 20 kHz), OAS soanrs (< 50 kHz), side scan sonars (75 kHz), distress sonars, mine avoidance sonars (80 kHz), and oceanographic application sonars, ADCP (75 kHz, 150 kHz, 300 kHz), sub bottom profilers (400 kHz) etc,. Hence the study of ambient noise demands a broad frequency spectrum.

Indian Ocean is known for monsoon and cyclonic activities as well as with the complex meso-scale and seasonal oceanographic conditions, this results in temporal and spatial variability of sound speed structure and hence in noise field. To understand the noise variability, continuous noise monitoring, covering entire water depth, at different locations are required. As these data collection experiments are difficult to install and maintain, and will be sparse in space and time, the need is to indigenously develop noise models which can stimulate noise variability in accordance with the prevailing environment and noise sources. The sources of ambient sound in different frequency bands include wind, rain, ship traffic and biological activities. Hence apart from environmental parameters noise models also require information on wind, rain, traffic and biomass.

This Ph.D work will cover the salient results on the sptio-temporal variability of the underwater soundscape through the modeling approach. Hence to address Indian Ocean noise variability, specific models representing different parts of noise spectrum for traffic and sea-state are attempted as part of the work. To model traffic related noise field parabolic equation based 2D PE-IFD model is implemented and to handle its 3D variability FOR3D model also implemented. For the simulation of wind induced noise field two models are implementing, Ray theory based CANARY and Normal mode based KRAKENC at different frequency bands.

Data model comparison in also included in the work to assess the performance of the implemented models other than Bench mark evaluation. In this regard noise data collected from different locations, along Indian coastal region covering major seasons of the location in both deep and shallow water. Analysis of in-situ noise data helped to quantify the actual seasonal and spatial variability of ambient noise in selected locations. To address the effect of oceanographic parameters on signal detection range (SDR) FOR3D model was utilized and quantified the variability in SDR with season and frequency at a selected shallow water location.