Tracking sound speed field under internal wave perturbation with the unscented Kalman filter

Model-based signal processing methods, such as matched-field processing, are concerned with exploiting the combination of the sound propagation physics in an ocean waveguide and the observation data. As such, they require accurate knowledge of the ocean acoustic environment. Tracking of environmental uncertainties is of great interest for model-based signal processing. This paper further develops the approach of acoustic data assimilation (ADA) for tracking the sound speed field under internal wave perturbations. Specifically, the sequential method of the UKF is used to implement the ADA for solving the nonlinear tracking problem. The simulation results demonstrate the validity of the developed approach.