Optimal sidelobes reduction and synthesis of circular array antennas using hybrid adaptive genetic algorithms

Abstract EN

In this article, a hybrid optimization method has been proposed consisting of adaptive genetic algorithms (AGAs) and constrained nonlinear programming (NLP) to solve the problems of performance optimization of circular array antenna consisting parallel center feeding short dipoles elements with two complex nonlinear optimization problems.

In the first problem, the hybrid optimization algorithm is used to reduce the value of sidelobe level in the circular array radiation pattern by finding the optimal values of the excitation coefficients of each element in the circular array.

In the second problem, a synthesis of circular array with different forms of the desired radiation pattern is considered.

Several examples are considered here to verify the validity of this method.

Comparisons were made between the results of this method and the results obtained by (SGA) standard genetic algorithm, and it is clearly shown that this method is more efficient and flexible in solving the problems of performance optimization of circular array antenna.