The optimization of sparse concentric ring array using differential evolution algorithm

Abstract

Sparse concentric ring array synthesis usually needs to meet a variety of constraints, namely the array aperture, the number of elements and the minimum element spacing maintain a fixed value. A dimensionality reduction method which is based on improved differential evolution algorithm is presented aiming at the problem of multi constraint optimization. The use of locally optimal mutation strategy accelerates the convergence speed of the algorithm, improves local search ability of differential evolution algorithm and the population diversity, solves the premature convergence problem. At the same time, the proposed method transforms the positions of two-dimensional concentric ring arrays optimization design into one-dimensional linear array, realizes the joint optimization of all the array elements, reduces algorithm complexity, while ensures the array side lobe performance. Simulation results establish the effectiveness of the method.