Far field from near field measurements. An approach to solve the inverse problem of electromagnetic radiation via genetic algorithms
DOI:
https://doi.org/10.17533/udea.redin.13752Keywords:
far field, near field, measurements, genetic algorithmsAbstract
In this paper the application of the Genetic Algorithms (GA) as a search method of a geometric configuration of elementary dipoles that solve the inverse problem of electromagnetic radiation are reported. The inverse problem of electromagnetic radiation appears as a new application in the electromagnetic compatibility area that allows estimating the far field radiation from near field measurements.
Downloads
References
C. A. Balanis. Antenna Theory Analysis and Design. 2ª. ed. Ed. Wiley. New York. 1987. pp. 134-207.
R. Laroussi, G. Costache. “Far-Field Predictions from Near-Field Measurements Using an Exact Integral Equation Solution”. IEEE Trans on EMC. Vol. 36. 1994. pp. 189-195. DOI: https://doi.org/10.1109/15.305453
W. D. Rawle. “The Method of Moments: A numerical Technique for Wire Antenna Design”. High Frequency
Electronics. Vol. 5. 2006. pp. 42-47. DOI: https://doi.org/10.2136/sh2006.3.0042
C. M. Coleman, J. Rothwell, J. E. Ross. “Investigation of Simulated Annealing, Ant-Colony Optimization and
Genetic Algorithms for Self-Structuring Antenna”. IEEE Trans on Antennas and Propagation. Vol. 52. 2004. pp. 1007-1014. DOI: https://doi.org/10.1109/TAP.2004.825658
T. S. Sijher, A. A. Kishk. “Antenna Modeling by Infinitesimal Dipoles Using Genetics Algorithms”. Progress in Electromagnetics Research PIER. Vol. 52. 2005. pp. 225-254. DOI: https://doi.org/10.2528/PIER04081801
B. Liu, L. Beghou, L. Pichon. “Adaptive Genetic Algorithm Based Source Identification with Near-Field Scanning”. Progress in Electromagnetics Research B. Vol. 9. 2008. pp. 215-230. DOI: https://doi.org/10.2528/PIERB08070904
D. E. Goldberg. Genetic Algorithms. Ed. Addison Wesley. New York. 1989. pp. 126-129.
R. L. Haupt. “An Introduction to Genetic Algorithms for Electromagnetics”. IEEE Antennas and Propagation Magazine. Vol. 37. 1995. pp. 7-15. DOI: https://doi.org/10.1109/74.382334
A. Rangel Merino, J. L. López Bonilla Linares, R. Miranda. “Optimization Method based on Genetic Algorithms”. Apeiron. Vol. 12. 2005. pp. 393-408.
Matlab 7.0. R14. 2004.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2018 Revista Facultad de Ingeniería
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Revista Facultad de Ingeniería, Universidad de Antioquia is licensed under the Creative Commons Attribution BY-NC-SA 4.0 license. https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
The material published in the journal can be distributed, copied and exhibited by third parties if the respective credits are given to the journal. No commercial benefit can be obtained and derivative works must be under the same license terms as the original work.