Synthesis of Antenna Array Using Modified Particle Swarm Optimization Technique
K. Prasanna Kumar1, M.G.V. Kishore2, K.V. Hemanth3, L. Sreekar4
1K.Prasanna Kumar, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
2M.G.V. Kishore, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
3K.V. Hemanth, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
4L.Sreekar, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 859-863 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3197038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper the synthesis of array antennas is done using modified particles swarm optimization technique (PSO) to minimize side lobe levels. This algorithm helps in higher performance, capable to solve general N-dimensional linear and non-linear optimization problems. The Modified PSO algorithm is easily conceivable, can be implemented using simple mathematical modelling when comparing with other evolutionary algorithms such as Genetic Algorithm (GA), Invasive weed optimization (IWO). The algorithm is formulated to suppress the side lobes level (SLL). By performing multiple iterations, we yield local best position and from that local best position we yield global best position of the particle and it is applied to the Synthesis of antenna arrays. The simulation pattern shows the optimal pattern of array antenna which is able to approach the desired pattern. The results demonstrated that the modified Particles swarm optimization algorithm is superior to the conventional PSO algorithm.
Keyword: Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Sidelobe Level, Array Antenna.
Scope of the Article: Discrete Optimization