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A model of an artificial neural network for frequency dependence of radar cross section
Author(s) -
Liu Hongwei,
Antar Yahia M. M.,
Wu Zhengde
Publication year - 1999
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/(sici)1098-2760(19990305)20:5<315::aid-mop10>3.0.co;2-7
Subject(s) - radar cross section , artificial neural network , microwave , radar , cross section (physics) , engineering , section (typography) , computer science , algorithm , artificial intelligence , physics , telecommunications , quantum mechanics , operating system
During recent years, the artificial neural network (ANN) has been applied to electromagnetic (EM) engineering as a fast and flexible method for modeling, simulation, and optimization. In this paper, an ANN model for the frequency dependence of a radar cross section (RCS) is proposed and trained by means of the measured data. Using this trained ANN model, the frequency dependence of an RCS can be extended to a lower or higher frequency region. The extended results are in reasonably good agreement with the measured and computed results by the optical model published. ©1999 John Wiley & Sons, Inc. Microwave Opt Technol Lett 20: 315–318, 1999.