Correction of the arc array excitation using genetic algorithm
Бесплатный доступ
The method of correction the discrete phase distribution of the circular arc phased array for alignment of bearing directions of the navigation radio beacons is proposed. Switchboarding step-scanning pattern of the arc array is accompanied by subscanning for given minimal discrete scan angle. The exact technique to determine the amplitude and phase distributions for the arc array excitation is proposed. This technique include both the mutual coupling of the array radiators and influence of the current distribution on cylindrical surface, over array is located. Numerical method for reducing size of the system of linear algebraic equiations is developed. This system due to corresponding summarize-integral equiations. It is shown that discretization of finding phase distribution (amplitude distribution is fixed) leads to inaccurate bearing directions of navigation radio beacons. For correcting the phase distribution is used the genetic algorithm, which has some advantages over traditional techniques of optimization. The results of modeling the subscanning mode shows practical utility and efficiency of the proposed correcting technique.
Arc phased array, summarize-integral equiations, discrete phase distribution, correcting genetic algorithm
Короткий адрес: https://sciup.org/147155143
IDR: 147155143 | DOI: 10.14529/ctcr160414
Список литературы Correction of the arc array excitation using genetic algorithm
- Hansen R.C. Phased Array Antennas. J. Wiley & Sons, 2009, 560 p DOI: 10.1002/9780470529188
- Voitovich N.I., Khashimov A.B. On the Correspondence of Asymptotic Solutions to 2D and 3D Problems in Antenna Engineering. Journal of Communications Technology and Electronics, 2010, vol. 55, no. 12, pp. 1374-1379 DOI: 10.1134/S1064226910120077
- Khashimov A.B., Salikhov R.R., Al’metov R.S. . Bulletin of the South Ural State University. Computational Mathematics and Software Engineering, 2014, vol. 3, no. 2, pp. 77-91. (in Russ.)
- Coleman T.F., Li Y. On the Convergence of Reflective Newton Methods for Large-Scale Nonlinear Minimization Subject to Bounds. Mathematical Programming, 1994, vol. 67, no. 2, pp. 189-224 DOI: 10.1007/BF01582221
- Melanie M. An Introduction to Genetic Algorithms. Massachusetts, MIT Press Cambridge, 1996, pp. 87-117.