Near Field to Far Field Conversion for an Infinite Ground Micro-Strip Trace Using Genetic Algorithm
Keywords:
Genetic algorithm, microstrip, near field to far field transformationAbstract
In this paper, an efficient combination of the near field to far field (NF-FF) transformation and the genetic algorithm (GA) is suggested for investigating of a microstrip trace on an infinite ground plane. Parameters of a set of ideal electric and magnetic dipoles are estimated by GA based on finite samples of near field data in the radiation region. Then, the far field pattern is determined, using the electromagnetic (EM) fields of equivalent ideal dipoles. The commercial software Ansoft High Frequency Structure Simulator (HFSS) is used for both, computing the near field data and validation of the proposed method. In addition, the influence of number of dipoles on the convergence rate is studied.
Downloads
References
V. P. Kodali, Engineering Electromagnetic Compatibility, IEEE press, 2001.
H. Fan and F. Schlagenhaufer, “Source identification and correlation between near field-far field tolerances when applying a genetic algorithm,” EMC Europe Int. Symp. EMC, Hamburg, pp. 587- 592, Sept. 2008.
H. Fan, “Using radiating near field region to sample radiation of microstrip traces for far field prediction by genetic algorithms, ”IEEE Microwave And Wireless Components Letters, vol. 19, no. 5, May 2009.
H. Fan and F. Schlagenhaufer, “Near field far field transformation for loops based on genetic algorithm,” Proc. 4th
H. Fan and F. Schlagenhaufer, “Near field far field conversion based on genetic algorithm for predicting radiation from PCBs,” Proc. IEEE Int. Symp. Electromag. Compat., Honolulu, HI, pp. 1-6, July 2007. Asia-Pacific Conf. Environ. Electromag, Dalian, China, pp. 476-481, Aug. 2006.
H. Fan and F. Schlagenhaufer, “Improvements of robustness of genetic algorithm for near field -far field radiation conversion,” Proc. IEEE Int. Symp. Microw., Antenna, Propag. EMC Technol. Wireless Commun., Hangzhou, China, pp. 950-953, Aug. 2007.
H. Fan and F. Schlagenhaufer, “Investigation of near field data sampling approaches for far field radiation prediction of PCBs by genetic algorithm,” Proc. 18th
D. E. Goldberg, Genetic Algorithms in Search, Optimization & Machine Learning. Reading, MA: Addison-Wesley, 1989. Int. Zurich Symp. Electromag. Compat., Munich, Germany, pp. 21-24, Sep. 2007.
Z. Michalewicz, Genetic Algorithm Data Structures, Evolution Programs, Berlin, Germany: Springer-Verlag, 1992.
J. M. Johnson and Y. Rahmat-Samii, “Genetic algorithms in engineering electromagnetics,” IEEE Antennas and Propagation Magazine, vol. 39, no. 4, August 1997.