An Optimization of Subarrayed Planar Array Pattern via Fractal Structure Thinning

Abstract

Dividing large planar arrays into several subarrays and then turning off some of them reduces the complexity (cost) of the system significantly. In this paper, two optimization stages for the formation of planar subarrays and the removal of some of them are proposed. The first optimization stage improves the pattern of the original planar array after dividing it into a set of rotational square and rectangular subarrays. In the second optimization stage, it works to remove some of the subarrays completely or partially, depending on new fractal structures derived from the conventional Sierpinski carpet structure. The proposed fractal-thinned planar array is based on amplitude-only excitation, i.e., the phases of the elements are set to zero. To execute the optimization steps above, a genetic algorithm (GA) is used. Some determinants are included in the optimization process to maintain the properties of the desired pattern. Simulation results showed the effectiveness of the proposed optimization method in achieving almost the same performance in both stages of optimization.