Abstract
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.
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Recommended by Associate Editor Yang Shi
Weisheng Yan is a professor at the School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China. His research interests include guidance and control of underwater vehicles, fault detection and fault-tolerant control.
Wei Chen received the B.S. and M.S. degrees from the Northwestern Polytechnical University, Xi’an, China, in 2010 and 2013, respectively. He is a Ph.D. candidate in the Northwestern Polytechnical University. His research interests include positioning of underwater vehicles, simultaneous input and state estimation.
Rongxin Cui is an associate professor at the School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China. His research interests include cooperative control of multiagent systems, path planning, control theory and applications.
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Yan, W., Chen, W. & Cui, R. Moving long baseline positioning algorithm with uncertain sound speed. J Mech Sci Technol 29, 3995–4002 (2015). https://doi.org/10.1007/s12206-015-0845-z
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DOI: https://doi.org/10.1007/s12206-015-0845-z