Notice of Violation of IEEE Publication PrinciplesUnderwater vehicle terrain navigation based on maximum likelihood estimation

Notice of Violation of IEEE Publication Principles

"Underwater Vehicle Terrain Navigation Based on Maximum Likelihood Estimation,"
by Tian Feng-min, Xu Ding-jie, Zhao Yu-xin and Li Ning,
in the Proceedings of the 2008 International Conference on Information and Automation, pp. 1268-1273

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.

This paper contains portions of original text from the paper cited below. The original text was copied without attribution.
"Terrain Navigation for Underwater Vehicles,"
by Ingemar Nygren, Phd Thesis, School of Electrical Engineering, Royal Institute of Technology, Sweden, December 2005Terrain aided navigation (TAN) is a way to improve underwater vehicle self navigation ability, which is essentially a nonlinear state estimation problem. The iterative Bayesian method based on maximum a posteriori (MAP) estimation has theoretic advantage in solving such problems. But due to the particularities of underwater vehicles, in some cases the long time continual filter is not suitable for underwater vehicles, where MAP estimation degenerates to maximum likelihood (ML) estimation, and continual filter changes to discontinuous positioning. By analyzing the shape of likelihood function, we found that the influence of false peaks in terrain matching will decrease with the increase of measuring beams, which proves the validity of ML estimation as a positioning method. Then a practical method of obtaining the measuring beams is proposed. Simulations validate these conclusions.