Abstract
In this paper, an improved differential evolution (DE) algorithm with the successful-parent-selecting (SPS) framework, named SPS-JADE, is applied to the pattern synthesis of linear antenna arrays. Here, the pattern synthesis of the linear antenna arrays is viewed as an optimization problem with excitation amplitudes being the optimization variables and attaining sidelobe suppression and null depth being the optimization objectives. For this optimization problem, an improved DE algorithm named JADE is introduced, and the SPS framework is used to solve the stagnation problem of the DE algorithm, which further improves the DE algorithm’s performance. Finally, the combined SPS-JADE algorithm is verified in simulation experiments of the pattern synthesis of an antenna array, and the results are compared with those obtained by other state-of-the-art random optimization algorithms. The results demonstrate that the proposed SPS-JADE algorithm is superior to other algorithms in the pattern synthesis performance with a lower sidelobe level and a more satisfactory null depth under the constraint of beamwidth requirement.
Highlights
An array of sensors or antennas, compared with a single one, often displays better characteristics and can perform more functions
The SPS framework used in the algorithm solves the stagnation problem which occurs in various differential evolution (DE) algorithms
The SPS-JADE algorithm is applied to the pattern synthesis of a 40-element linear symmetric antenna array with the sidelobe suppression and null depth under the beamwidth constraint of optimizing the excitation amplitudes of array elements
Summary
An array of sensors or antennas, compared with a single one, often displays better characteristics and can perform more functions. Since the end of the 20th century, with the rapid development of computer technology, more and more random optimization algorithms have been applied to the antenna design These highly flexible algorithms have few restrictions on the optimization objectives, which make them suitable to solve complicated and nonlinear optimization problems, and they show a better optimization performance and a higher degree of freedom in antenna array pattern. An SPS-JADE algorithm for antenna array pattern syntheses is designed by combining the aforementioned JADE algorithm with the SPS framework This algorithm can find the optimal solution with fewer iteration numbers, and it is verified in the pattern synthesis simulations for the antenna arrays with more elements.
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