  This paper presents a robust non-linear state estimator for autonomous
surface vehicles, where the movement is restricted to the horizontal plane. It
is assumed that only the vehicle position and orientation can be measured,
being the former affected by bounded noises. Then, under some fair standard
assumptions concerning the maximum velocities and acceleration rates of the
vehicle, the estimator is able to reconstruct not only the velocities, but also
the lumped generalised disturbances, that cluster external disturbances,
non-linearities, and unmodelled dynamics. The observer is easily tunable by the
user, with a set of four scalars, two of them related to the velocity of
convergence of the estimator, and the other two parameters to set the desired
trade-off between noise sensitivity and disturbance rejection. Several
simulations with a well-known test-bed craft are provided to show how the
proposed algorithm outperforms previous ones in the literature.
