Dynamic estimation of the sound-speed field in Mediterranean coastal waters

The acoustic monitoring of space- and time-dependent structures in coastal waters constitutes a complex inverse problem which is attractive to physical oceanography. In this work the use of a nonlinear Kalman filtering scheme is investigated for tracking the evolution of the sound-speed field in a vertical section of a shallow water environment, taking into account the bottom acoustic properties. In support of the MREA/BP´07 experiment southeast of Elba, Italy, prediction results from the NCOM oceanic model provide realistic scenarios to test the tracking algorithm. Constraints in the form of range- distributed observations such as the sea surface temperature (SST) are added in an attempt to obtain uniqueness of the solu tion. This paper shows that the formulation of the range-resolving inverse problem in a state-space model allows implementing a Kalman-based processor that effectively track the time variations of the 2-D sound-speed field. Furthermore, the estimations are enhanced by using an unscented Kalman filter (UKF) in place of the standard extended Kalman filter (EKF).