Sound speed and attenuation in muddy sediments from low-frequency acoustic measurements

2017 ◽  
Vol 142 (4) ◽  
pp. 2556-2556
Author(s):  
Lin Wan ◽  
Mohsen Badiey ◽  
D. P. Knobles ◽  
Preston S. Wilson ◽  
Justin Eickmeier
Keyword(s):  
Sound Speed ◽  
Low Frequency ◽  
Acoustic Measurements ◽  
Muddy Sediments

Inferring low-frequency compressional sound speed and attenuation in muddy sediments from long-range broadband sound propagation

2018 ◽  
Vol 144 (3) ◽  
pp. 1947-1947
Author(s):  
Lin Wan ◽  
Mohsen Badiey ◽  
David P. Knobles ◽  
Preston S. Wilson
Keyword(s):  
Long Range ◽  
Sound Speed ◽  
Sound Propagation ◽  
Low Frequency ◽  
Muddy Sediments ◽  
Broadband Sound

scholarly journals Depth Discrimination for Low-Frequency Sources Using a Horizontal Line Array of Acoustic Vector Sensors Based on Mode Extraction

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3692 ◽  
Author(s):  
Guolong Liang ◽  
Yifeng Zhang ◽  
Guangpu Zhang ◽  
Jia Feng ◽  
Ce Zheng
Keyword(s):  
Sound Speed ◽  
Linear Equations ◽  
Robustness Analysis ◽  
Low Frequency ◽  
Horizontal Line ◽  
Testing Hypotheses ◽  
Depth Discrimination ◽  
Line Array ◽  
Vector Sensors ◽  
Mode Extraction

Depth discrimination is a key procedure in acoustic detection or target classification for low-frequency underwater sources. Conventional depth-discrimination methods use a vertical line array, which has disadvantage of poor mobility due to the size of the sensor array. In this paper, we propose a depth-discrimination method for low-frequency sources using a horizontal line array (HLA) of acoustic vector sensors based on mode extraction. First, we establish linear equations related to the modal amplitudes based on modal beamforming in the vector mode space. Second, we solve the linear equations by introducing the total least square algorithm and estimate modal amplitudes. Third, we select the power percentage of the low-order modes as the decision metric and construct testing hypotheses based on the modal amplitude estimation. Compared with a scalar sensor, a vector sensor improves the depth discrimination, because the mode weights are more appropriate for doing so. The presented linear equations and the solution algorithm allow the method to maintain good performance even using a relatively short HLA. The constructed testing hypotheses are highly robust against mismatched environments. Note that the method is not appropriate for the winter typical sound speed waveguide, because the characteristics of the modes differ from those in downward-refracting sound speed waveguide. Robustness analysis and simulation results validate the effectiveness of the proposed method.

Low‐frequency acoustic measurements at Los Alamos

1994 ◽  
Vol 96 (5) ◽  
pp. 3334-3334
Author(s):  
Rodney W. Whitaker
Keyword(s):  
Low Frequency ◽  
Acoustic Measurements ◽  
Los Alamos

Shipboard low frequency sound speed measurements in the New England Mud Patch

2016 ◽  
Vol 139 (4) ◽  
pp. 2111-2111
Author(s):  
Gabriel R. Venegas ◽  
Preston S. Wilson ◽  
Kevin M. Lee ◽  
Megan S. Ballard ◽  
Allen H. Reed ◽  
...  
Keyword(s):  
New England ◽  
Sound Speed ◽  
Low Frequency ◽  
Frequency Sound

Finite element modeling of the low-frequency sound speed of seagrass leaves

2020 ◽  
Vol 148 (4) ◽  
pp. 2482-2483
Author(s):  
Nicholas A. Torres ◽  
Megan S. Ballard ◽  
Kevin M. Lee ◽  
Gabriel R. Venegas ◽  
Preston S. Wilson
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Sound Speed ◽  
Low Frequency ◽  
Frequency Sound ◽  
Element Modeling
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