scholarly journals Estimating marine sediment attenuation at low frequency with a vertical line array

2009 ◽  
Vol 125 (4) ◽  
pp. EL158-EL163 ◽  
Author(s):  
Yong-Min Jiang ◽  
N. Ross Chapman ◽  
Kunde Yang ◽  
Yuanliang Ma
Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3462 ◽  
Author(s):  
Chunyu Qiu ◽  
Shuqing Ma ◽  
Yu Chen ◽  
Zhou Meng ◽  
Jianfei Wang

A method is developed in this paper to calculate the spatial gain of a vertical line array when the plane-wave assumption is not applicable and when the oceanic ambient noise is correlated. The proposed optimal array gain (OAG), which can evaluate the array’s performance and effectively guide its deployment, can be given by an equation in which the noise gain (NG) is subtracted from the signal gain (SG); hence, a high SG and a negative NG can enhance the performance of the array. OAGs and SGs with different array locations are simulated and analyzed based on the sound propagation properties of the direct-arrival zone (DAZ) and the reliable acoustic path (RAP) using ray theory. SG and NG are related to the correlation coefficients of the signals and noise, respectively, and the vertical correlation is determined by the structures of the multipath arrivals. The SG in the DAZ is always high because there is little difference between the multipath waves, while the SG in the RAP changes with the source-receiver range because of the variety of structure in the multiple arrivals. The SG under different conditions is simulated in this work. The “dual peak” structure can often be observed in the vertical directionality pattern of the noise because of the presence of bottom reflection and deep sound channel. When the directions of the signal and noise are close, the conventional beamformer will enhance the correlation of not only the signals but also the noise; thus, the directivity of the signals and noise are analyzed. Under the condition of having a typical sound speed profile, the OAG in some areas of the DAZ and RAP can achieve high values and even exceed the ideal gain of horizontal line array 10 logN dB, while, in some other areas, it will be lowered because of the influence of the NG. The proposed method of gain analysis can provide analysis methods for vertical arrays in the deep ocean under many conditions with references. The theory and simulation are tested by experimental data.


Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1315 ◽  
Author(s):  
Hui Li ◽  
Kunde Yang ◽  
Rui Duan ◽  
Zhixiong Lei

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3692 ◽  
Author(s):  
Guolong Liang ◽  
Yifeng Zhang ◽  
Guangpu Zhang ◽  
Jia Feng ◽  
Ce Zheng

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.


2008 ◽  
Vol 123 (5) ◽  
pp. 3349-3349
Author(s):  
Alireza Amiri‐Simkooei ◽  
Mirjam Snellen ◽  
Dick G. Simons ◽  
Michael Buckingham

2018 ◽  
Vol 143 (1) ◽  
pp. EL8-EL12 ◽  
Author(s):  
Kunde Yang ◽  
Liya Xu ◽  
Qiulong Yang ◽  
Rui Duan

1998 ◽  
Vol 103 (5) ◽  
pp. 2909-2909
Author(s):  
Kevin D. Heaney ◽  
Peter N. Mikhalevsky

1999 ◽  
Vol 106 (4) ◽  
pp. 2133-2133
Author(s):  
Tracianne B. Neilsen ◽  
Evan K. Westwood
Keyword(s):  

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