Abstract
Terrain-aided navigation (TAN) is one of the most effective approaches for solving the long-range navigation of autonomous underwater vehicles. However, the positioning accuracy of TAN can be greatly influenced by the terrain information of matching areas. A TAN system might also fail catastrophically when the seabed topography changes. To address these problems, a dynamic path planning method for TAN, which includes environment modelling, offline path planning, and online re-planning, is proposed in this paper. Terrain standard deviation is applied to represent terrain information in environment modelling, and the Mahalanobis distance and roulette approach are introduced in the offline path planning approach. Furthermore, the topographic changes are identified and handled via an online re-planning approach. Simulation experiments are conducted, and comparisons are made with the A* algorithm. According to the experimental results, the proposed method improves the positioning accuracy of TAN during the mission, and its ability to deal with seabed topographic changes is also verified.
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