Notice of Violation of IEEE Publication Principles: Modeling Evaporation Duct Propagation above Gaussian Rough Sea Surface by the Parabolic Wave Equation

Notice of Violation of IEEE Publication Principles

"Modeling Evaporation Duct Propagation above Gaussian Rough Sea Surface by the Parabolic Wave Equation"
by Pan Yue, Ma Yuanling, and Yang Kunde
in the International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE 2007), 2007, pp. 786 – 789

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 significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:

"Forward Propagation Modeling Above Gaussian Rough Surfaces By The Parabolic Wave Equation: Introduction Of The Shadowing Effect"
by V. Fabbro, C. Bourlier, P.F. Combes
in Progress In Electromagnetics Research, PIER 58, 2006, pp. 243 – 269


A fast and accurate method is presented that accounts for polarization and Gaussian rough surface effects over the sea for evaporation ducting conditions using the Split Step Fourier (SSF) Parabolic Wave Equation (PWE). The method is based on the Discrete Mixed Fourier Transform (DMFT), in which the Miller-Brown reflection coefficient is replaced by the rigorous rough surface reflection coefficient, so the shadowing effect is included. Evaporation duct propagation above Gaussian rough sea surfaces is modeled with the method in the paper. By comparison to the current propagation model, the method validates the more accurate position of extreme value of the propagation loss and reduces over-prediction.