Moving long baseline positioning algorithm with uncertain sound speed

This paper presents a Moving long baseline (MLBL) positioning algorithm for the underwater target considering the uncertain underwater sound speed. First, the positioning and the sound speed models are established. To tackle the uncertain sound speed, a Uncertain least squares (ULS) positioning algorithm is applied to estimate the target position and the sound speed. Then it is essentially shown that four mobile buoys are necessarily (at least) required to locate the target. Further, it is found that under a singularity scenario in which the ranges between the target and each of the mobile buoys are equal, there is no solution to the positioning according to the classical geometrical equations. In order to solve this singularity problem, an ULS-based Unscented Kalman filter (UKF) algorithm is proposed to obtain the estimated solution. Simulation results illustrate the effectiveness of proposed methods.