Boundary Pass underwater listening station cabled hydrophone array system

2021 ◽  
Vol 150 (4) ◽  
pp. A123-A123
Author(s):  
David E. Hannay ◽  
Art Cole ◽  
Jack Hennessey
Keyword(s):  
Hydrophone Array

scholarly journals Estimation of the Noise Source Level of a Commercial Ship Using On-Board Pressure Sensors

2021 ◽  
Vol 11 (3) ◽  
pp. 1243
Author(s):  
Hongseok Jeong ◽  
Jeung-Hoon Lee ◽  
Yong-Hyun Kim ◽  
Hanshin Seol
Keyword(s):  
Noise Source ◽  
Pressure Sensors ◽  
Low Frequency ◽  
Frequency Resolution ◽  
Source Strength ◽  
Recording Time ◽  
Source Level ◽  
The One ◽  
Hydrophone Array ◽  
Good Agreement

The dominant underwater noise source of a ship is known to be propeller cavitation. Recently, attempts have been made to quantify the source strength using on-board pressure sensors near the propeller, as this has advantages over conventional noise measurement. In this study, a beamforming method was used to estimate the source strength of a cavitating propeller. The method was validated against a model-scale measurement in a cavitation tunnel, which showed good agreement between the measured and estimated source levels. The method was also applied to a full-scale measurement, in which the source level was measured using an external hydrophone array. The estimated source level using the hull pressure sensors showed good agreement with the measured one above 400 Hz, which shows potential for noise monitoring using on-board sensors. A parametric study was carried out to check the practicality of the method. From the results, it was shown that a sufficient recording time is required to obtain a consistent level at high frequencies. Changing the frequency resolution had little effect on the result, as long as enough data were provided for the one-third octave band conversion. The number of sensors affected the mid- to low-frequency data.

Sound source location by difference of phase, on a hydrophone array with small dimensions

2001 ◽  
Vol 109 (1) ◽  
pp. 430-433 ◽  
Author(s):  
Karsten Brensing ◽  
Katrin Linke ◽  
Dietmar Todt
Keyword(s):  
Sound Source ◽  
Source Location ◽  
Hydrophone Array

Spatial rotation-based direction-of-arrival estimation for uniform circular hydrophone array

2021 ◽  
Vol 178 ◽  
pp. 107945
Author(s):  
Yu Hao ◽  
Nan Zou ◽  
Longhao Qiu ◽  
Chenmu Li ◽  
Yan Wang ◽  
...  
Keyword(s):  
Direction Of Arrival ◽  
Direction Of Arrival Estimation ◽  
Spatial Rotation ◽  
Hydrophone Array

scholarly journals Azimuth Tracking of Underwater Moving Sound Source Based on Time Delay Estimation Using Hydrophone Array

2017 ◽  
Vol 170 ◽  
pp. 169-176 ◽  
Author(s):  
Dhany Arifianto ◽  
Wirawan ◽  
B.T. Atmaja ◽  
Tutug Dhanardhono ◽  
Saptian A. Rahman
Keyword(s):  
Time Delay ◽  
Sound Source ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Moving Sound Source ◽  
Hydrophone Array

scholarly journals Results from an autonomous underwater vehicle towed hydrophone array experiment in Nantucket Sound

2006 ◽  
Vol 120 (2) ◽  
pp. EL15-EL21 ◽  
Author(s):  
Jason D. Holmes ◽  
William M. Carey ◽  
D. Keith Wilson ◽  
James F. Lynch ◽  
D. Keith Wilson
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Hydrophone Array

scholarly journals Travel-time correction and preliminary results for ocean acoustic tomography in South China Sea

2019 ◽  
Vol 283 ◽  
pp. 04003
Author(s):  
Xingyu Ji ◽  
Hangfang Zhao
Keyword(s):  
Kalman Filter ◽  
South China Sea ◽  
Travel Time ◽  
South China ◽  
Sound Speed ◽  
Acoustic Tomography ◽  
Speed Profile ◽  
Travel Times ◽  
Sound Speed Profile ◽  
Hydrophone Array

An acoustic tomography trial experiment was conducted in South China Sea during May to August in 2016. Two moorings are installed apart from about 56.94 km, while each consists of one low frequency source, 20 hydrophones deployed from the depth of about 400 m to 1600 m, total 32 depth sensors and 3 compass and tilt sensors. Due to internal waves and currents in this area, as a typical value, horizontal drift of a mooring can reach 300 m, thus moorings drift need to be considered to correct ray travel-time. In this paper, the shape of a mooring is estimated firstly and locations of all hydrophone array elements are then calculated and finally used to determine travel-time perturbation of acoustic arrivals. The mooring is modelled as 2 curves, while the end of the mooring is fixed at the cement anchor on the sea floor. Optimization is used to acquire hydrophone location inferential solution. The inferred shape of hydrophone array and element locations are used to correct the travel-times measured in the experiment. We find that corrected travel-times match the trend of the change of sound speed profile better in the sea. Finally, the corrected travel-times are used to tomography of sound speed profile. AR (Autoregressive) process is used to describe the dynamic evolution of sound speed profile and Kalman filter is applied in the sequential estimation. The performances of the time-independent method and the method using AR process and Kalman filter are compared, reasonably the latter is better than the former in particular with abundant measured data.

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