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International Journal of Antennas and Propagation
Volume 2015, Article ID 713080, 10 pages
http://dx.doi.org/10.1155/2015/713080
Research Article

Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

1Department of Electrical and Electronics Engineering, Faculty of Engineering, Nuh Naci Yazgan University, 38040 Kayseri, Turkey
2Department of Electricity and Energy, Vocational College, Erciyes University, 38039 Kayseri, Turkey

Received 14 January 2015; Accepted 27 March 2015

Academic Editor: Miguel Ferrando Bataller

Copyright © 2015 Kerim Guney and Ali Durmus. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

An evolutionary method based on backtracking search optimization algorithm (BSA) is proposed for linear antenna array pattern synthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and phase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical examples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and flexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm optimization (PSO), genetic algorithm (GA), modified touring ant colony algorithm (MTACO), quadratic programming method (QPM), bacterial foraging algorithm (BFA), bees algorithm (BA), clonal selection algorithm (CLONALG), plant growth simulation algorithm (PGSA), tabu search algorithm (TSA), memetic algorithm (MA), nondominated sorting GA-2 (NSGA-2), multiobjective differential evolution (MODE), decomposition with differential evolution (MOEA/D-DE), comprehensive learning PSO (CLPSO), harmony search algorithm (HSA), seeker optimization algorithm (SOA), and mean variance mapping optimization (MVMO). The simulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.