Dual-angle Iterative Algorithm for Rotationally Asymmetrical Surface Deviation Reconstruction

A new algorithm to reconstruct rotationally asymmetrical surface deviation is proposed. In planar absolute tests, single-angle iterative algorithm is used to retrieve rotationally asymmetrical surface deviation. However, it always encounters the problem that certain azimuthal frequency terms either do not converge or converge too slowly. In this paper, the convergence characteristics of the single-angle iterative algorithm are analyzed, and it is found that the convergence rate is related to the rotation angle and azimuthal frequency magnitudes. In order to solve the convergence problem, dual-angle iterative algorithm is proposed which uses two rotation measurement data. And the method of obtaining the optimal second rotation angle is presented. Simulation experiments prove that compared to the single-angle iterative algorithm, the dual-angle iterative algorithm can enhance the convergence rate and improve the reconstruction accuracy.