|Feature-oriented acoustic tomography for coastal ocean observatories|Carriere, O.; Hermand, J.-P. (2013). Feature-oriented acoustic tomography for coastal ocean observatories. IEEE J. Ocean. Eng. 38(3): 534-546. dx.doi.org/10.1109/JOE.2012.2227543
In: IEEE Journal of Oceanic Engineering. IEEE: New York. ISSN 0364-9059, more
Coastal acoustic tomography; inversion; Kalman filter; random walk;range dependent; sequential Bayesian filtering; thermal front; upwelling
The deployment of coastal observatories motivates the development of acoustic inversion schemes able to characterize rapidly time-varying range-dependent environments. This paper develops feature models as parameterization schemes for the range-dependent temperature field, when the latter is mainly influenced by an identified oceanic feature, here thermal fronts. The feasibility of feature-oriented acoustic tomography (FOAT) is demonstrated in two cases of coastal thermal front known to occur regularly: the Ushant tidal front, France (48.5 ° N, 5 ° E), and the Cabo Frio coastal upwelling, Brazil (23 ° S, 42 ° W). Realistic scenarios simulated with regional circulation models provide typical environmental variations for testing the validity of the FOAT approach, with both global optimization and sequential filtering of the (synthetic) full-field acoustic data. Matched-field processing at multiple frequencies is used to reduce ambiguities between parameters and to achieve a good tradeoff between robustness and sensitivity. The proposed feature-model parameterization is shown to provide robust estimates of the 2-D temperature field even when the simulated environment presents smaller scale inhomogeneities. Moreover, the sequential filtering based on a random walk model of the thermal front parameters enables a stable tracking of typical temperature field variations along several days. This sequential approach is particularly convenient for continuous, long-term monitoring operated with bottom-moored ocean observatories.