A deep‐ocean hydrophone array

Abstract Spectral amplitudes of direct P and P coda between 0.5 and 6 Hz have been measured for 14 Eastern Kazakh test explosions using 8 hydrophones of the Wake Island Array, and a new model for these data has been developed to estimate relative yields of those explosions. Each log spectral amplitude is considered to be the sum of four parameters and an error term. Three parameters are frequency-dependent and represent: (1) the average Eastern Kazakh spectrum at the Wake Island Array; (2) the spectral shape characteristics unique to each event; and (3) the station or hydrophone corrections. The fourth parameter represents relative yield. A total of 346 parameters, including the 14 relative yields, were needed to model all 901 spectral amplitudes that were measured, and first-order linear regression techniques were used to invert the data for these parameters. Standard deviations of the computed relative yields are very small, averaging only 0.015 mb units. Deviations between the relative yields and their corresponding relative NEIS body-wave magnitudes, however, are larger, averaging 0.14 mb units. This difference is interpreted to be an indicator of the level of inhomogeneity in the worldwide pattern of energy radiated from Eastern Kazakh tests. There is evidence that this pattern can be correlated with the precise epicentral location of each explosion within the test site and is due to focusing and defocusing near the source. It is proposed that the yield of a large explosion might be disguised by siting the explosion at a location that selectively defocuses energy towards continents where most seismic stations are located. The precision with which a relative yield is determined from the data of any single hydrophone averages 0.035 mb units. Thus, the model appears to provide a very stable measure of yield. Errors associated with frequencies greater than 2 Hz are only slightly greater than errors associated with frequencies less than 2 Hz, verifying the utility of using the higher frequencies observed in direct P and P coda to estimate yield.

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Deep‐ocean hydrophone array

The Journal of the Acoustical Society of America ◽

10.1121/1.381413 ◽

1977 ◽

Vol 61 (5) ◽

pp. 1147-1152

Author(s):

John A. Behrens ◽

Robert H. Stokes

Keyword(s):

Deep Ocean ◽

Hydrophone Array

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Po/So phases: Propagation velocity across a 1,500-km-long, deep ocean hydrophone array.

Journal of Physics of the Earth ◽

10.4294/jpe1952.35.111 ◽

1987 ◽

Vol 35 (2) ◽

pp. 111-125 ◽

Cited By ~ 6

Author(s):

Daniel Alvin WALKER ◽

Charles Stoddard McCREERY

Keyword(s):

Propagation Velocity ◽

Deep Ocean ◽

Hydrophone Array

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Localization of Two Sound Sources Based on Compressed Matched Field Processing with a Short Hydrophone Array in the Deep Ocean

Sensors ◽

10.3390/s19173810 ◽

2019 ◽

Vol 19 (17) ◽

pp. 3810 ◽

Cited By ~ 2

Author(s):

Ran Cao ◽

Kunde Yang ◽

Qiulong Yang ◽

Peng Chen ◽

Quan Sun ◽

...

Keyword(s):

Greedy Algorithm ◽

Source Localization ◽

Signal To Noise Ratio ◽

Deep Ocean ◽

Spatial Filter ◽

Sound Sources ◽

Matched Field Processing ◽

Array Aperture ◽

Hydrophone Array ◽

The Greedy Algorithm

Passive multiple sound source localization is a challenging problem in underwater acoustics, especially for a short hydrophone array in the deep ocean. Several attempts have been made to solve this problem by applying compressive sensing (CS) techniques. In this study, one greedy algorithm in CS theory combined with a spatial filter was developed and applied to a two-source localization scenario in the deep ocean. This method facilitates localization by utilizing the greedy algorithm with a spatial filter at several iterative loops. The simulated and experimental data suggest that the proposed method provides a certain localization performance improvement over the use of the Bartlett processor and the greedy algorithm without a spatial filter. Additionally, the effects on the source localization caused by factors such as the array aperture, number of hydrophones or snapshots, and signal-to-noise ratio (SNR) are demonstrated.

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