Range-resolving shallow water acoustic tomography by ensemble Kalman filtering

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.