Optimal Side Lobes Reduction of Linear Array Antenna Using Crow Search Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 7
Abstract
The aim of this paper is to introduce the novel metaheuristic crow search Optimization algorithm (CSA) to the electromagnetic and antenna community. Crow search algorithm is a population based method, mimicking the intelligent behavior of crows to proceed to a global solution. In this paper, CSA has been employed for the pattern optimization of linear antenna array by elements amplitude only and position only synthesis. Different designs examples are presented that illustrate the effectiveness of CSA for linear array optimization; so as to obtain an array pattern with minimum side lobe level (SLL) along with null placement in the specified directions. The results of CSA are validated by benchmarking them with the results obtained by ant lion optimization (ALO), particle swarm optimization (PSO) and grey wolf optimization (GWO) etc. Here, peak SLL and deep nulls obtained from crow search algorithm are improved up to -38 dB and -105 dB, respectively. These Simulation results suggest that using CSA may lead to finding promising results compared to the other algorithms in terms of solution accuracy, easy to implement and convergence rate.
Authors and Affiliations
Jaspreet Kaur, Dr. Sonia Goyal
Keywords
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