Simulating the lateral line with low-frequency nearfield acoustic holography based on a vector hydrophone array for short-range navigation in littoral waters

2015 ◽  
Vol 138 (3) ◽  
pp. 1897-1897 ◽  
Author(s):  
Tim Ziemer
Keyword(s):  
Lateral Line ◽  
Short Range ◽  
Low Frequency ◽  
Acoustic Holography ◽  
Vector Hydrophone ◽  
Hydrophone Array ◽  
Nearfield Acoustic Holography

Localizing Swimming Objects in Noisy Environments by Applying Nearfield Acoustic Holography and Minimum Energy Method

2015 ◽  
Author(s):  
Tim Ziemer
Keyword(s):  
Energy Method ◽  
Marine Mammals ◽  
Minimum Energy ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Acoustic Holography ◽  
Robust Detection ◽  
Array Measurements ◽  
Minimum Energy Method ◽  
Nearfield Acoustic Holography

A problem in localizing individual swimming objects acoustically is the high amount of strongly fluctuating ambient noise due to turbulent pressure fluctuations, thermal and seismic noise, motoring vessels, wind and marine mammals. In littoral and other shallow waters additionally the complex boundaries produce absorption of high-frequency components and strong reverberation in other frequency regions, refraction due to sudden changes in temperature and scattering from the rough sea surface and floor. In this paper localization of a single swimming object in presence of disturbing sources and noise is simulated. Low-frequency nearfield acoustic holography (NAH) based on vector hydrophone array measurements is combined with minimum energy method (MEM) to increase detection certainty. This combination of NAH and MEM appears to be a reliable and robust detection method suitable e.g. for sort-range navigation in littoral waters and for iceberg detection in open waters.

A Study on the Fine Structure of the Lateral Line Organ of the Sea Eel

1973 ◽  
Vol 31 ◽  
pp. 648-649
Author(s):  
K. Hama
Keyword(s):  
Fine Structure ◽  
Electron Microscope ◽  
Lateral Line ◽  
Low Frequency ◽  
Sensory Cells ◽  
Apical Surface ◽  
Voltage Electron ◽  
Sensory Epithelia ◽  
Low Frequency Vibration ◽  
Transmission Electron

The lateral line organs of the sea eel consist of canal and pit organs which are different in function. The former is a low frequency vibration detector whereas the latter functions as an ion receptor as well as a mechano receptor.The fine structure of the sensory epithelia of both organs were studied by means of ordinary transmission electron microscope, high voltage electron microscope and of surface scanning electron microscope.The sensory cells of the canal organ are polarized in front-caudal direction and those of the pit organ are polarized in dorso-ventral direction. The sensory epithelia of both organs have thinner surface coats compared to the surrounding ordinary epithelial cells, which have very thick fuzzy coatings on the apical surface.

scholarly journals Design and implementation of a jellyfish otolith-inspired MEMS vector hydrophone for low-frequency detection

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Renxin Wang ◽  
Wei Shen ◽  
Wenjun Zhang ◽  
Jinlong Song ◽  
Nansong Li ◽  
...  
Keyword(s):  
Structural Parameters ◽  
Low Frequency ◽  
Directivity Pattern ◽  
Stress Distributions ◽  
Strong Response ◽  
Underwater Acoustic ◽  
Frequency Detection ◽  
Vector Hydrophone ◽  
Shock Resistance ◽  
Marine Applications

AbstractDetecting low-frequency underwater acoustic signals can be a challenge for marine applications. Inspired by the notably strong response of the auditory organs of pectis jellyfish to ultralow frequencies, a kind of otolith-inspired vector hydrophone (OVH) is developed, enabled by hollow buoyant spheres atop cilia. Full parametric analysis is performed to optimize the cilium structure in order to balance the resonance frequency and sensitivity. After the structural parameters of the OVH are determined, the stress distributions of various vector hydrophones are simulated and analyzed. The shock resistance of the OVH is also investigated. Finally, the OVH is fabricated and calibrated. The receiving sensitivity of the OVH is measured to be as high as −202.1 dB@100 Hz (0 dB@1 V/μPa), and the average equivalent pressure sensitivity over the frequency range of interest of the OVH reaches −173.8 dB when the frequency ranges from 20 to 200 Hz. The 3 dB polar width of the directivity pattern for the OVH is measured as 87°. Moreover, the OVH is demonstrated to operate under 10 MPa hydrostatic pressure. These results show that the OVH is promising in low-frequency underwater acoustic detection.

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.

scholarly journals An Improved Squirrel Search Algorithm for Maximum Likelihood DOA Estimation and Application for MEMS Vector Hydrophone Array

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 118343-118358 ◽  
Author(s):  
Peng Wang ◽  
Yujun Kong ◽  
Xuefang He ◽  
Mingxing Zhang ◽  
Xiuhui Tan
Keyword(s):  
Maximum Likelihood ◽  
Search Algorithm ◽  
Doa Estimation ◽  
Vector Hydrophone ◽  
Hydrophone Array

scholarly journals Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6949
Author(s):  
Zhibo Shi ◽  
Guolong Liang ◽  
Longhao Qiu ◽  
Guangming Wan ◽  
Lei Zhao
Keyword(s):  
Compressed Sensing ◽  
Array Signal Processing ◽  
Simultaneous Optimization ◽  
L1 Norm ◽  
Array Design ◽  
Vector Hydrophone ◽  
Grid Algorithm ◽  
The Difference ◽  
Acoustic Environments ◽  
Hydrophone Array

Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the design of the vector hydrophone array. The difference between the vector hydrophone array and the scalar hydrophone array is that each vector hydrophone has three or four channels. When designing a sparse vector hydrophone array, these channels need to be optimized at the same time to ensure the sparsity of the array elements’ number. To solve this problem, this paper introduced the compressed sensing (CS) theory into the vector hydrophone array design, constructed the vector hydrophone array design problem into a globally solvable optimization problem, proposed a CS-based algorithm with the L1 norm suitable for vector hydrophone array, and realized the simultaneous optimization of multiple channels from the same vector hydrophone. At the same time, the off-grid algorithm was added to obtain higher design accuracy. Two design examples verify the effectiveness of the proposed method. The theoretical analysis and simulation results show that compared with the conventional compressed sensing algorithm with the same aperture, the algorithm proposed in this paper used fewer vector hydrophone elements to obtain better fitting of the desired beam pattern.

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