Terrain matching positioning method for underwater vehicles based on curvature discrimination

Abstract

Terrain matching positioning technology is used to locate underwater vehicles by the terrain information. The traditional method uses all real-time bathymetric points to traverse the underwater prior map, which has a large calculation amount and high complexity. To improve computational efficiency while ensuring accuracy, we represent the terrain matching positioning method based on the local terrain features and the global search technology in this paper. Firstly, the Moving Least Square (MLS) method is used to construct the MLS surface of the multi-beam bathymetric terrain. Then, a shape operator related to the principal curvatures is employed to reflect the curvedness of the MLS surface at each bathymetric point. Next, a Local Curvature Binary Discrimination (LCBD) method is proposed to describe the shape of local MLS surface with a LCBD descriptor, and divide the points satisfying the LCBD situations into the sampling point set. Finally, the Genetic Algorithm (GA) is introduced to replace the traditional traversal method (TM) to search the optimal estimated position of vehicle from the underwater prior map. The experimental results show that the proposed method can quickly locate the vehicle without affecting the accuracy, and the efficiency is improved by more than 80% compared with the traditional method.