Optimal synthesis of linear antenna arrays using a harmony search algorithm

Authors:
K. Guney;M. Onay
Affiliations:
Department of Electrical and Electronics Engineering, Faculty of Engineering, Nuh Naci Yazgan University, Kayseri, Turkey;Department of Aircraft Electrical and Electronics, Civil Aviation School, Erciyes University, 38039 Kayseri, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 4
Cited 0

Antenna-array pattern nulling using a differential evolution algorithm: Original Articles

International Journal of RF and Microwave Computer-Aided Engineering
Amplitude-only pattern nulling of linear antenna arrays with the use of an immune algorithm

International Journal of RF and Microwave Computer-Aided Engineering
Music-Inspired Harmony Search Algorithm: Theory and Applications

Music-Inspired Harmony Search Algorithm: Theory and Applications
Bees algorithm for interference suppression of linear antenna arrays by controlling the phase-only and both the amplitude and phase

Expert Systems with Applications: An International Journal

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Abstract

A method based on harmony search algorithm (HSA) for the pattern synthesis of linear antenna arrays with the prescribed nulls is presented. Nulling of the pattern is achieved by controlling the amplitude-only, the phase-only, and the position-only. The HSA is conceptualized using the musical process of searching for a perfect state of harmony. To show the effectiveness of the proposed HSA, several examples of linear antenna array patterns with the imposed single, multiple and broad nulls are given. It is found that the nulling method based on HSA is capable of steering the array nulls precisely to the undesired interference directions. The results of HSA are compared with the results of the modified touring ant colony optimization (MTACO), the bees algorithm (BA), the bacterial foraging algorithm (BFA), the plant growth simulation algorithm (PGSA), the clonal selection algorithm (CLONALG), the particle swarm optimization (PSO), the quadratic programming method (QPM), the tabu search algorithm (TSA), the genetic algorithm (GA), the memetic algorithm (MA), the nondominated sorting genetic algorithm 2 (NSGA-2), the multiobjective differential evolution (MODE), and the multiobjective evolutionary algorithms based on decomposition with differential evolution (MOEA/D-DE).