Sparse rectangular planar array antenna synthesis based on improved grey wolf optimizer algorithm and window function weighting

Aiming at the optimization problem of sparsely distributed rectangular planar array antenna under the constraints of array aperture, number of array elements and minimum array element spacing, a synthesis method of sparsely distributed rectangular planar array antenna based on improved grey wolf optimizer (IGWO) algorithm and window function weighting is proposed. Firstly, the grey wolf optimizer (GWO) algorithm is improved by Tent chaotic mapping, nonlinear convergence factor, dominant wolf dynamic confidence strategy and opposition-based learning strategy to increase the population diversity and the ability of the algorithm to jump out of the local optimal. Then, the window function is used to weight the array elements to generate the location distribution matrix, which reduces the time of sparse matrix optimization and improves the optimization efficiency. Finally, the location distribution matrix is used to generate sparse array, and then the IGWO algorithm is used to optimize the thinly distributed under multiple constraints. Simulation experiments are carried out to verify the effectiveness of the proposed method. The experimental results show that the proposed method can effectively improve the performance of the array antenna and reduce the peak sidelobe level. This integrated method is of engineering significance and reference value for solving array distribution problems under multiple constraints.