Dynamic Estimation of the Sound-Speed Profile from Broadband Acoustic Measurements

Global search and more recently adjoint-based inversion methods used in ocean acoustics showed their effectiveness in the estimation of the sound-speed profile (SSP) in water columns of several environments. In the framework of the European Seas Observatory Network (ESONET) an essential part of the research and technology focuses on continuous and long term observations to characterize dynamic ocean processes and monitor the global state of the ocean. Therefore, the development of high performance integrated tools for acoustic inversion is one of the attractive components in this network. For the purpose of efficient data assimilation this paper investigates sequential methods that are able to update sound-speed profile parameters, typically the coefficients of empirical orthogonal functions (EOF), with respect to new incoming acoustic or hydrographic measurements and take into account the seafloor and sub-seafloor acoustic properties in a shallow water environment. A formulation using Kalman filters is suitable for a sequential treatment. This paper investigates the application of two different extensions of the Kalman filter, the extended Kalman filter and the more recent unscented Kalman filter for comparison.