Joint Estimation of Gravity Anomaly and Vertical Motion of a Marine Vehicle

The paper discusses the problem of optimal joint estimation of gravity anomalies and the vertical motion of a marine vehicle, including its inertial accelerations, in terms of Bayesian approach. This estimation problem is solved using Kalman filtering and smoothing algorithms, including the adaptive ones. Potential estimation accuracy of the algorithms and their sensitivity to inaccurate setting of the model parameters are studied. Bayesian and traditional time-invariant (stationary) estimation algorithms for filtering and smoothing are compared.