Sparse Circular Array Optimization Using Genetic Algorithm

An Improved Genetic Algorithm is presented in this paper to solve the problem of optimum element position design of sparse circular arrays with multiple constraints. The initial feasible solutions for genetic algorithm (GA) which meet multiple design constraints are produced from the framework concerning element position of uniform concentric circular arrays. And let these solutions act as the thinning chromosome, which is used to describe the element distribution of the sparse circular arrays. By utilizing the IGA, a smaller searching space can be achieved, and the freedom of the element can be exploited. Finally, the simulation is done and the numerical results confirm the great efficiency and the robustness of the new algorithm.