scholarly journals Retrieval of deterministic normal modes from cross-correlations of acoustic noise in shallow water

2015 ◽  
Author(s):  
Andrey S. Shurup ◽  
Sergei N. Sergeev ◽  
Valeriy V. Goncharov ◽  
Alexander I. Vedenev ◽  
Oleg A. Godin ◽  
...  
Keyword(s):  
Shallow Water ◽  
Acoustic Noise ◽  
Normal Modes ◽  
Cross Correlations

Separation of acoustic normal modes in shallow water

2021 ◽  
Vol 149 (4) ◽  
pp. A66-A67
Author(s):  
Sergei Sergeev ◽  
Konstantin Dmitriev ◽  
Andrey Shurup
Keyword(s):  
Shallow Water ◽  
Normal Modes

Coupling of acoustic normal modes in shallow water

1982 ◽  
Vol 71 (S1) ◽  
pp. S11-S11
Author(s):  
Suzanne T. McDaniel
Keyword(s):  
Shallow Water ◽  
Normal Modes

Underwater Acoustic Noise Model for Shallow Water Communications

2012 ◽  
Author(s):  
José Panaro ◽  
Fábio Lopes ◽  
Leonardo Barreira ◽  
Fidel Souza
Keyword(s):  
Shallow Water ◽  
Acoustic Noise ◽  
Noise Model ◽  
Underwater Acoustic

A DEDISPERSION TRANSFORM FOR SOUND PROPAGATION IN SHALLOW WATER WAVEGUIDE

2010 ◽  
Vol 18 (03) ◽  
pp. 245-257 ◽  
Author(s):  
DA ZHI GAO ◽  
NING WANG ◽  
HAO ZHONG WANG
Keyword(s):  
Fourier Transform ◽  
Data Processing ◽  
Shallow Water ◽  
Sound Propagation ◽  
Normal Modes ◽  
Real Data ◽  
Present Approach ◽  
Dispersive Effect

For sound propagation in a shallow water waveguide, a dedispersion transform which can remove the dispersive effect of signal is described in this paper. The transform is a modified Fourier transform with two variables: translation and dispersion. Dispersive effect of signal for normal modes can be removed when these two variables match to real parameters. The validity of the present approach is verified in simulation and real data processing.

scholarly journals PENGGUNAAN LIDAR (LIGHT DETECTION AND RANGING) UNTUK MENGUKUR KEDALAMAN PERAIRAN DANGKAL

OSEANA ◽  
2019 ◽  
Vol 44 (1) ◽  
pp. 54-69
Author(s):  
Hollanda A Kusuma ◽  
Nadya Oktaviani
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Acoustic Noise ◽  
Light Detection And Ranging ◽  
Light Detection ◽  
Bathymetric Data ◽  
Depth Data ◽  
Remote Sensing Technology ◽  
Research Activities ◽  
Sensing Technology

UTILIZATION OF LIDAR (LIGHT DETECTION AND RANGING) TO MEASURE SHALLOW WATER DEPTH. Understanding on seabed characteristics such as the topography, composition and habitat conditions was very important to provide information not only for shipping activities, conservation, management and planning activities, but also for research activities with accurate bathymetry data. Accurate bathymetric data can be obtained from hydrographic surveys and remote sensing technology analysis. The hydrographic survey is used to obtain bathymetry data by applying singlebeam echosounder (SBES) and multibeam echosounder (MBES). At a depth of <15m (shallow water) was difficult to carry out an acoustic survey. At present there is one remote sensing technology that can be used to support hydrographic surveys namely Bathymetric LIDAR (Light Detection and Ranging). LIDAR was able to detect objects on land and waters due to being flown by a vehicle. Wide LIDAR sweep makes data acquisition faster and more effective than acoustic noise. Therefore, LIDAR was an alternative to obtain depth data, especially in coastal areas with a depth of less than 50 m.

Acoustic Noise Generated on a Shallow-Water Shelf by Vessels with Electric Motors

2020 ◽  
Vol 66 (5) ◽  
pp. 517-527
Author(s):  
A. N. Rutenko ◽  
M. Yu. Fershalov ◽  
V. G. Ushchipovskii
Keyword(s):  
Shallow Water ◽  
Acoustic Noise ◽  
Electric Motors
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