Variable step size adaptive cuckoo search optimization algorithm for phase diversity

The phase diversity (PD) algorithm will eventually be converted into a large-scale nonlinear numerical optimization problem, so the selection of numerical optimization algorithm will directly determine the accuracy and speed of the algorithm settlement. In this paper, we introduce the cuckoo search optimization algorithm, which has the advantages of simple model, few parameters, and easy implementation, to the phase diversity algorithm. By improving the step size control factor in the original cuckoo search algorithm, we can make it have faster optimization speed for PD. In the simulation experiments, we further proved and gave a simple explanation in theory that in the case of large-scale wavefront sensing, compared to the traditional particle swarm algorithm, this improved algorithm has higher accuracy and faster convergence speed. Finally, we set up a simple experimental system and proved the effectiveness of the improved cuckoo search algorithm for PD.