Synthesis of Sparse Linear Arrays With Reduced Excitation Control Numbers Using a Hybrid Cuckoo Search Algorithm With Convex Programming

Abstract

Sparse linear arrays based on a novel subarrayed scheme are proposed and synthesized in this letter. The array with a fixed aperture size is partitioned into several uniformly spaced subarrays while number, spacing, and excitation in each subarray are optimized with multiple constraints. Compared with conventional sparse linear array with all the elements excited independently, the sparse linear array with the novel subarrayed scheme provides excitations at the subarray port and reduces the excitation control numbers remarkably. By integrating the cuckoo search (CS) algorithm with convex programming (CP), a hybrid CS–CP method is proposed and applied to the synthesis problem while the constraints are satisfied during the optimization process. Three examples with series of cases are presented, and the obtained results are compared to those presented in some state-of-the-art references. The optimized array achieves an improved peak sidelobe level and reduced excitation control number.