Skip to main content
Publications | Persons | Institutes | Projects
[ report an error in this record ]basket (0): add | show Print this page

Range-resolving shallow water acoustic tomography by ensemble Kalman filtering
Carriere, O.; Hermand, J.P.; Candy, J.V. (2008). Range-resolving shallow water acoustic tomography by ensemble Kalman filtering, in: MTS et al. Oceans 2008 MTS/IEEE Quebec. Oceans, Poles & Climate: Technological Challenges, September 15-18, 2008, Quebec City, Canada. Oceans (New York), 1-4: pp. 964-968
In: MTS; IEEE (Ed.) (2008). Oceans 2008 MTS/IEEE Quebec. Oceans, Poles & Climate: Technological Challenges, September 15-18, 2008, Quebec City, Canada. Oceans (New York), 1-4. IEEE: New York. ISBN 978-1-4244-2619-5. , more
In: Oceans (New York). IEEE: New York. ISSN 0197-7385, more
Peer reviewed article  

Available in  Authors 
Document type: Conference paper

Keyword
    Marine/Coastal
Author keywords
    coastal acoustic tomography; nonlinear Kalman filter; empirical

Authors  Top 
  • Carriere, O., more
  • Hermand, J.P., more
  • Candy, J.V.

Abstract
    In the context of the recent Maritime Rapid Environmental Assessment sea trial (MREA/BP'07), this paper presents a range-resolving tomography method based on the ensemble Kalman filtering (EnKF) of full-field acoustic measurements on a vertical array. The measurements are assimilated in a Gauss-Markov model of the sound-speed field time variations with known statistics. The reformulation of the inverse problem in an ocean data assimilation framework enables the sequential tracking of time- and space-varying environmental parameters. The tracking scheme is here applied to a realistic simulation of a vertical slice in a shallow water environment. Sea-surface sound-speed measurements are augmented to the measurement vector to constrain the range-dependent structure. Known bottom and subbottom properties are taken into account in the propagation model. When compared to the extended Kalman filter, the EnKF is shown to properly cope with the nonlinearity introduced by the full-field approach.

All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy Top | Authors