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Passive vector geoacoustic inversion in coastal areas using a sequential unscented Kalman filter

An unscented Kalman filter (UKF) for geoacoustic inversion using scalar and vector sound fields created by a passing ship is discussed in this paper. The continuous sound field emitted by a ship of opportunity is processed by the sequential filtering technique to estimate slowly changing environmental properties along the source range. The inversion problem is solved by the UKF with a random-walk parameter model, which is expected to perform well when dealing with highly nonlinear problems. Synthetic geoacoustic inversions are performed using multi-frequency pressure, vertical particle velocity and waveguide impedance (a ratio between pressure and vertical particle velocity) data for the geoacoustic model of a mud environment offshore at the mouth of the Amazon River in Brazil (CANOGA 12). For the preliminary tests, the sound source is composed of a flat spectrum. Numerical results demonstrate that the sequential filtering technique is capable of estimating the evolution of environmental properties along the source range. In practice, ship data have complex time-varying spectral characteristics that can greatly limit the accuracy of broadband or multi-frequency passive applications. Since the vertical waveguide impedance is independent of the source spectral level, it is preferred for environmental characterization by the sound field generated from a ship of opportunity. Because of this independence property, the vertical waveguide impedance is expected to yield a more reliable inversion than that of pressure or vertical particle velocity field.