Spatial variation of ocean ambient noise spectrum in offshore China

2016 ◽  
Vol 140 (4) ◽  
pp. 3351-3351
Author(s):  
Guoli Song ◽  
Xinyi Guo ◽  
Li Ma ◽  
Qianchu Zhang
Keyword(s):  
Spatial Variation ◽  
Ambient Noise ◽  
Noise Spectrum

Vector Ocean Ambient Noise Spectrum Simulation Based on Parabolic Equation Model in Shallow Water

2017 ◽  
Vol 25 (02) ◽  
pp. 1750034
Author(s):  
Liufang Fu ◽  
Peng Li ◽  
Xinhua Zhang ◽  
Shuqing Ma ◽  
Chengzhi Gao
Keyword(s):  
Parabolic Equation ◽  
South China Sea ◽  
Particle Velocity ◽  
South China ◽  
Ambient Noise ◽  
Sound Pressure ◽  
Noise Spectrum ◽  
China Sea ◽  
Simulation Results ◽  
Horizontal Particle

Ocean ambient noise spectrum is one of the most important characteristics of ambient noise. An ocean vector ambient noise field model was built up based on parabolic equation in this paper. Then the spectra of sound pressure, horizontal particle velocity and vertical particle velocity were calculated applying the model considering noise sources well distributed on the surface with typical summer sound speed profile in South China Sea. The simulation results showed that spectra of sound pressure, horizontal particle velocity and vertical particle velocity were obviously not varied with depth. Then, the simulated results were compared with the experiment results at the receiving depth of a trail in South China Sea in July 2012. Compared with the experimental results, the simulation results are consistent well with the experimental one of sound pressure and horizontal particle velocity in the trend. But the simulation values at low frequency band below 500[Formula: see text]Hz, are not consistent with the experimental one very well, in the band the simulation results are lower than the experimental by about 3–5[Formula: see text]dB. But the simulation result of vertical particle velocity was not consistent with the experimental one, illustrating that the precision of the model might not be enough in the vertical direction.

A Real-Time Processing Method of Underwater Ambient Noise Spectrum Based on One-Third Octave

2013 ◽  
Vol 333-335 ◽  
pp. 522-525
Author(s):  
Chao Ma ◽  
Chun Jie Qiao ◽  
Yue Ke Wang ◽  
Shen Zhao
Keyword(s):  
Real Time ◽  
Ambient Noise ◽  
Noise Spectrum ◽  
Processing Method ◽  
Real Time Processing ◽  
Time Processing ◽  
Object A ◽  
Passive Detection ◽  
Continuous Measuring ◽  
Underwater Object

Extended, continuous measuring and analysis for underwater ambient noise can find the objects like ships and submarine. It is important for passive detection of underwater object. A real-time processing method of one-third octave spectrum is presented. It is shown by tests that the method is steady and satisfy the real-time processing.

scholarly journals Noise Model Analysis and Estimation of Effect due to Wind Driven Ambient Noise in Shallow Water

2011 ◽  
Vol 2011 ◽  
pp. 1-4 ◽  
Author(s):  
S. Sakthivel Murugan ◽  
V. Natarajan ◽  
R. Rajesh Kumar
Keyword(s):  
Wind Speed ◽  
Marine Mammals ◽  
Ambient Noise ◽  
Signal Transmission ◽  
Acoustic Signals ◽  
Noise Spectrum ◽  
Noise Model ◽  
Frequency Range ◽  
Entire Frequency Range ◽  
Wind Speeds

Signal transmission in ocean using water as a channel is a challenging process due to attenuation, spreading, reverberation, absorption, and so forth, apart from the contribution of acoustic signals due to ambient noises. Ambient noises in sea are of two types: manmade (shipping, aircraft over the sea, motor on boat, etc.) and natural (rain, wind, seismic, etc.), apart from marine mammals and phytoplanktons. Since wind exists in all places and at all time: its effect plays a major role. Hence, in this paper, we concentrate on estimating the effects of wind. Seven sets of data with various wind speeds ranging from 2.11 m/s to 6.57 m/s were used. The analysis is performed for frequencies ranging from 100 Hz to 8 kHz. It is found that a linear relationship between noise spectrum and wind speed exists for the entire frequency range. Further, we developed a noise model for analyzing the noise level. The results of the empirical data are found to fit with results obtained with the aid of noise model.

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