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 sy...
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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.
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