Synthesis of Cosecant Squared Pattern based on Convex Optimization

In this paper, a convex optimization method has been proposed for synthesizing a cosecant squared pattern(CSP). By taking the autocorrelation function of weight vector and the maximum ripple level as the optimization variables, and changing the non-convex optimization to convex optimization problem through variable substitution, the optimal autocorrelation function can be achieved, and then we can obtain the array weight vector. Some detailed simulations are presented and results show that compared to particle swarm optimization (PSO) method, the proposed method has fewer ripples in the shaped region and lower sidelobe (SLL).