Aperture Resource Optimization Method for Low Sidelobe Linear Opportunistic Array Based on PSO-CVX Algorithm

Abstract

In this paper, a joint optimization method is proposed that comprehensively considers the low sidelobe pattern synthesis problem and the aperture resource saving problem of linear opportunistic array. Firstly, the fuzzy stochastic simulation algorithm is used to solve the uncertainty in the chance-constrained programming model. Then the particle swarm optimization algorithm is used to select the working array elements. As the array aperture is fixed, the convex optimization algorithm is used as the local algorithm to obtain the best excitation coefficient. The simulation results show that the algorithm proposed in this paper can obtain lower sidelobe level under the condition of saving aperture resources.