GES long baseline navigation with unknown sound velocity and discrete-time range measurements

A common assumption in long baseline (LBL) underwater acoustic navigation is that the speed of sound is available. This quantity depends on the medium and it is usually measured or profiled prior to the experiments. This paper proposes a novel filtering solution that explicitly takes into account the estimation of the speed of propagation of the acoustic waves in the medium. Based on discrete-time range measurements, an augmented system is derived that can be regarded as linear for observability and observer design purposes. Its observability is discussed and a Kalman filter provides the estimation solution, with globally exponentially stable (GES) error dynamics. Simulation results are presented, considering noisy measurements, to evaluate the proposed solution, which evidence both fast convergence and good performance.