Modified GA Optimization of Linear Sparse Array

With a goal to optimize the element positions to reduce the peak sidelobe level (PSLL) of the array pattern, a modified real Genetic Algorithms (MGA) for the synthesis of sparse linear arrays is described. The multiple optimization constrains include the number of elements, the aperture and the minimum element spacing. The advanced new approach reduces the size of the searching area of GA by means of indirect description of chromosome and avoids infeasible solution during the optimization process by designing the new genetic operators. The elementary steps of MGA are presented. The simulated results confirm the great efficiency and the robustness of this algorithm.