Optimization of Yagi-Uda Antenna Using Simulated Annealing

Simulated annealing (SA) is a stochastic global optimization technique, which has been used successfully for optimization of antenna arrays. In this paper, the use of SA for optimization of gain, impedance and bandwidth of the Yagi-Uda antenna has been presented. To evaluate the performance of designs, a method of moments code NEC2 has been used. Comparative results indicate superiority of using SA over other methods.

[1]  D. Cheng,et al.  Gain optimization for Yagi-Uda arrays , 1991, IEEE Antennas and Propagation Magazine.

[2]  J. Redvik.  Simulated annealing optimization applied to antenna arrays with failed elements , 1999, IEEE Antennas and Propagation Society International Symposium. 1999 Digest. Held in conjunction with: USNC/URSI National Radio Science Meeting (Cat. No.99CH37010).

[3]  David K. Cheng,et al.  Optimum element spacings for Yagi-Uda arrays , 1972 .

[4]  K. Guney,et al.  Amplitude-Only Pattern Nulling of Linear Antenna Arrays with the Use of Bees Algorithm , 2007 .

[5]  Y. Kuwahara,et al.  Multiobjective optimization design of Yagi-Uda antenna , 2005, IEEE Transactions on Antennas and Propagation.

[6]  Vittorio Murino,et al.  Synthesis of unequally spaced arrays by simulated annealing , 1996, IEEE Trans. Signal Process..

[7]  G. K. Mahanti,et al.  Phase-Only and Amplitude-Phase Only Synthesis of Dual-Beam Pattern Linear Antenna Arrays Using Floating-Point Genetic Algorithms , 2007 .

[8]  C. Ruf.  Numerical annealing of low-redundancy linear arrays , 1993 .

[9]  William T. Joines,et al.  Design of Yagi-Uda antennas using genetic algorithms , 1997 .

[10]  Ricardo H. C. Takahashi,et al.  The real-biased multiobjective genetic algorithm and its application to the design of wire antennas , 2003 .

[11]  David K. Cheng,et al.  Optimum element lengths for Yagi-Uda arrays , 1975 .

[12]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[13]  G. Burke,et al.  Numerical Electromagnetics Code (NEC)-Method of Moments. A User-Oriented Computer Code for Analysis of the Electromagnetic Response of Antennas and Other Metal Structures. Part 1: Program Description-Theory. Part 2: Program Description-Code. Volume 1. Revised , 1981 .

[14]  Ehl Emile Aarts,et al.  Simulated annealing and Boltzmann machines , 2003 .

[15]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[16]  Jing J. Liang,et al.  Design of Yagi-Uda antennas using comprehensive learning particle swarm optimisation , 2005 .

[17]  R.W.P. King,et al.  The linear antenna—Eighty years of prograss , 1967 .

[18]  A. Soares,et al.  Optimization of gain, impedance and bandwidth in Yagi-Uda antennas using genetic algorithm , 1999, 1999 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference.

[19]  Peter Salamon,et al.  Facts, Conjectures, and Improvements for Simulated Annealing , 1987 .

[20]  Christos N. Capsalis,et al.  ELECTRONIC BEAM STEERING USING SWITCHED PARASITIC SMART ANTENNA ARRAYS , 2002 .

[21]  Rob A. Rutenbar,et al.  Simulated annealing algorithms: an overview , 1989, IEEE Circuits and Devices Magazine.

[22]  Iti Saha Misra,et al.  Design, Analysis and Optimization of V-Dipole and its Three-Element Yagi-Uda Array , 2006 .

[23]  G. K. Mahanti,et al.  PHASE-ONLY AND AMPLITUDE-PHASE SYNTHESIS OF DUAL-PATTERN LINEAR ANTENNA ARRAYS USING FLOATING-POINT GENETIC ALGORITHMS , 2007 .

[24]  A. Massa,et al.  LINEAR ANTENNA SYNTHESIS WITH A HYBRID GENETIC ALGORITHM , 2004 .