scholarly journals Gradient field of undersea sound speed structure extracted from the GNSS-A oceanography: GNSS-A as a sensor for detecting sound speed gradient

2019 ◽  
Vol 1 (7) ◽  
Author(s):  
Yusuke Yokota ◽  
Tadashi Ishikawa
Keyword(s):  
Sound Speed ◽  
Gradient Field ◽  
Sound Speed Structure ◽  
Speed Gradient

Gradient field of undersea sound speed structure extracted from the GNSS-A oceanography

2018 ◽  
Vol 40 (4) ◽  
pp. 493-504 ◽  
Author(s):  
Yusuke Yokota ◽  
Tadashi Ishikawa ◽  
Shun-ichi Watanabe
Keyword(s):  
Sound Speed ◽  
Gradient Field ◽  
Sound Speed Structure

Observations of thermohaline sound speed structure in the Beaufort Sea in the summer of 2015

2015 ◽  
Vol 138 (3) ◽  
pp. 1743-1743
Author(s):  
Dominic DiMaggio ◽  
Annalise Pearson ◽  
John A. Colosi
Keyword(s):  
Sound Speed ◽  
Beaufort Sea ◽  
Sound Speed Structure

scholarly journals GARPOS: Analysis Software for the GNSS‐A Seafloor Positioning With Simultaneous Estimation of Sound Speed Structure

2020 ◽  
Vol 8 ◽  
Author(s):  
Shun-ichi Watanabe ◽  
Tadashi Ishikawa ◽  
Yusuke Yokota ◽  
Yuto Nakamura
Keyword(s):  
Sound Speed ◽  
Empirical Bayes ◽  
Information Criterion ◽  
Satellite System ◽  
Observation Equation ◽  
Simultaneous Estimation ◽  
Acoustic Ranging ◽  
Observation Network ◽  
Sound Speed Structure ◽  
Global Navigation Satellite

Global Navigation Satellite System–Acoustic ranging combined seafloor geodetic technique (GNSS-A) has extended the geodetic observation network into the ocean. The key issue for analyzing the GNSS-A data is how to correct the effect of sound speed variation in the seawater. We constructed a generalized observation equation and developed a method to directly extract the gradient sound speed structure by introducing appropriate statistical properties in the observation equation, especially the data correlation term. In the proposed scheme, we calculate the posterior probability based on the empirical Bayes approach using the Akaike’s Bayesian Information Criterion for model selection. This approach enabled us to suppress the overfitting of sound speed variables and thus to extract simpler sound speed field and stable seafloor positions from the GNSS-A dataset. The proposed procedure is implemented in the Python-based software “GARPOS” (GNSS-Acoustic Ranging combined POsitioning Solver).

Sign in / Sign up

Export Citation Format

Share Document