Sound Source Depth Estimation Based on Multipath Time Delay in Deep Water

2018 ◽  
Vol 104 (2) ◽  
pp. 363-368 ◽  
Author(s):  
Qiulong Yang ◽  
Kunde Yang
Keyword(s):  
Time Delay ◽  
Deep Water ◽  
Sound Source ◽  
Depth Estimation ◽  
Source Depth

Use of multipath time-delay ratio for source depth estimation with a vertical line array in deep water

2021 ◽  
Vol 149 (1) ◽  
pp. 524-539
Author(s):  
Hui Li ◽  
Zhezhen Xu ◽  
Kunde Yang ◽  
Rui Duan
Keyword(s):  
Time Delay ◽  
Deep Water ◽  
Depth Estimation ◽  
Vertical Line ◽  
Source Depth ◽  
Line Array

Formulas for Source Depth Estimation From Multipath Arrivals in Deep Water

2020 ◽  
Vol 56 (6) ◽  
pp. 4856-4871
Author(s):  
Rui Duan ◽  
Kunde Yang ◽  
Feiyun Wu ◽  
Yuanliang Ma
Keyword(s):  
Deep Water ◽  
Depth Estimation ◽  
Source Depth

A Simple Method for Source Depth Estimation with Multi-path Time Delay in Deep Ocean

2016 ◽  
Vol 33 (12) ◽  
pp. 124302 ◽  
Author(s):  
Kun-De Yang ◽  
Qiu-Long Yang ◽  
Xiao-Le Guo ◽  
Ran Cao
Keyword(s):  
Time Delay ◽  
Deep Ocean ◽  
Depth Estimation ◽  
Source Depth ◽  
Simple Method

A performance study of acoustic interference structure applications on source depth estimation in deep water

2019 ◽  
Vol 145 (2) ◽  
pp. 903-916 ◽  
Author(s):  
Rui Duan ◽  
Kunde Yang ◽  
Hui Li ◽  
Qiulong Yang ◽  
Feiyun Wu ◽  
...  
Keyword(s):  
Deep Water ◽  
Depth Estimation ◽  
Source Depth ◽  
Performance Study ◽  
Interference Structure ◽  
Acoustic Interference ◽  
A Performance

Source depth estimation using multi-station waveform data

1984 ◽  
Vol 74 (5) ◽  
pp. 1623-1643
Author(s):  
Falguni Roy
Keyword(s):  
Depth Estimation ◽  
The United States ◽  
Digital Data ◽  
United States Geological Survey ◽  
Travel Times ◽  
Source Depth ◽  
Time Data ◽  
Waveform Data ◽  
Level Ii ◽  
Level I

Abstract A depth estimation procedure has been described which essentially attempts to identify depth phases by analyzing multi-station waveform data (hereafter called level II data) in various ways including deconvolution, prediction error filtering, and spectral analysis of the signals. In the absence of such observable phases, other methods based on S-P, ScS-P, and SKS-P travel times are tried to get an estimate of the source depth. The procedure was applied to waveform data collected from 31 globally distributed stations for the period between 1 and 15 October 1980. The digital data were analyzed at the temporary data center facilities of the National Defense Research Institute, Stockholm, Sweden. During this period, a total number of 162 events in the magnitude range 3.5 to 6.2 were defined by analyzing first arrival time data (hereafter called level I data) alone. For 120 of these events, it was possible to estimate depths using the present procedure. The applicability of the procedure was found to be 100 per cent for the events with mb > 4.8 and 88 per cent for the events with mb > 4. A comparison of level I depths and level II depths (the depths as obtained from level I and level II data, respectively) with that of the United States Geological Survey estimates indicated that it will be necessary to have at least one local station (Δ < 10°) among the level I data to obtain reasonable depth estimates from such data alone. Further, it has been shown that S wave travel times could be successfully utilized for the estimation of source depth.

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 Striation-based source depth estimation with a vertical line array in the deep ocean

2018 ◽  
Vol 143 (1) ◽  
pp. EL8-EL12 ◽  
Author(s):  
Kunde Yang ◽  
Liya Xu ◽  
Qiulong Yang ◽  
Rui Duan
Keyword(s):  
Deep Ocean ◽  
Depth Estimation ◽  
Vertical Line ◽  
Source Depth ◽  
Line Array

A neural network for mode space source depth estimation

2005 ◽  
Vol 117 (4) ◽  
pp. 2463-2464
Author(s):  
William Lee ◽  
Yung Lee
Keyword(s):  
Neural Network ◽  
Depth Estimation ◽  
Source Depth ◽  
Mode Space
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