基于混合粒子群算法的相位差波前探测技术

Phase Diversity Wavefront Detection Technique Based on Hybrid Particle Swarm Algorithm

光学望远镜系统内部温度分布不均匀,镜面热变形等因素导致的离焦、球差等低阶大像差会严重降低光学系统的探测能力。给出了相位差法结合离焦光栅进行波前探测的原理,提出了权重线性递减的粒子群优化结合禁忌搜索的混合粒子群算法,并通过仿真验证了该算法的优化性能。采用相位差法结合离焦光栅采集两幅图像,然后通过混合粒子群算法求解目标函数,就可以重构波前,估计出波前像差。仿真结果表明,该算法可以实现对波前像差RMS值在0.859λ以下的目标函数的优化求解,优化后的波前残差达到10-3量级,并且迭代3次左右即可以完全收敛,满足低阶大像差的校正精度要求。

Lower-order large aberrations,such as defocusing and spherical aberrations,caused by uneven temperature distribution inside an optical telescope system and mirror thermal deformations,seriously reduce the detection capability of an optical system.Herein,a method for wavefront detection that combines the phase diversity method with defocusing grating is introduced.In addition,a hybrid particle swarm algorithm that combines a linear descending weight particle swarm optimization with tabu search is proposed.The optimization performance of the algorithm is verified by simulation.Two images are acquired using a combination of the phase diversity method and defocusing grating,enabling the wavefront to thereafter be reconstructed and the wavefront aberration to be estimated by solving the objective function using hybrid particle swarm algorithm.The simulation results show that the proposed algorithm can solve the objective function for the wavefront aberration with an RMS value below 0.859λ.After optimization,the wavefront residual error reaches the order of 10-3 and convergence is achieved after approximate 3 iterations.This result satisfies the correction accuracy of low-order large aberration.