OPTIMAL DESIGN OF SPARSE ARRAYS BASED ON MODIFIED QUANTUM GENETIC ALGORITHM

摘要

In order to reduce the peak sidelobe level (PSLL) of the linear array pattern, algorithm of linear array pattern optimization method is proposed based on margin space coding and quantum genetic algorithm (MS_QGA). Using the quantum genetic algorithm to optimize the position margin of array elements in the case that constrain the array aperture, the number of array elements and the minimum array elements space of the uniform linear array, and the optimization goal is to reduce the PSLL. The convergence speed of the proposed method is accelerated, the local search ability and the diversity of the population are improved to solve the premature convergence problem, the complexity of the method and the computation are reduced, the performance of PSLL of the sparse linear arrays is improved, and the array element is better distributed in the array aperture.