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Multipath Parallel ICCP Underwater Terrain Matching Algorithm Based on Multibeam Bathymetric Data
Author(s) -
Hanbing Wang,
Xiaosu Xu,
Tao Zhang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2866687
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Using the underwater terrain for assisted navigation is a popular research direction for autonomous underwater vehicle navigation technology. The iterated closest contour point (ICCP) algorithm is one of the classic matching algorithms in underwater terrain assisted navigation. However, the traditional ICCP algorithm is not suitable for the case of large initial error of inertial navigation system (INS) because it easily leads to a total match failure. This failure brings a great challenge to an underwater terrain matching system. In this paper, the improved ICCP underwater terrain matching algorithm, a multipath parallel ICCP algorithm, is proposed. The improved algorithm is based on multibeam bathymetric data acquired by the multibeam echosounder that is one of the main instruments of water depth measurement. The data points at the center and both sides of the edge of the swath sounding data are chosen to comprise three paths that are fully utilized by the improved algorithm. Computer simulation is used to evaluate the proposed algorithm in two terrain differences areas. Simulation results verify the effectiveness of multipath parallel ICCP algorithm. The proposed algorithm can effectively solve the problem of matching divergence caused by large initial errors of INS and obtain higher location accuracy.

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