基于鲸鱼-粒子群复合算法的子孔径拼接技术OA

To address the problems of slow convergence and susceptibility to local optima in particle swarm optimization(PSO)for sub-aperture stitching,a hybrid algorithm combining whale optimization algorithm(WOA)and PSO is proposed.In the early stage of iteration,the prey-searching mechanism of WOA is introduced to enhance the global search capability and reduce the risk of premature convergence.In the later stage,the bubble-net attacking strategy of WOA is incorporated to enrich the particle update mechanism and improve the local exploration of the solution space around the current optimum.Simulation tests based on wavefronts fitted by Zernike polynomials are carried out to compare the performance of PSO and WOA-PSO,and the results show that WOA-PSO achieves a faster convergence rate.Stitching experiments are further conducted on a 310 mm long optical flat using a laser flat interferometer with an aperture of 150 mm.When the translation step is 50 mm,the stitched result obtained by WOA-PSO exhibited a PV error of-0.040 4 λ and an RMS error of-0.021 3 λ relative to the full-aperture measurement result(λ=632.8 nm).The results demonstrate that the proposed algorithm can effectively compensate for inter-sub-aperture errors and accurately reconstruct the overall surface figure of the measured optical flat.