Intrinsic surface feature based subaperture stitching of freeform wavefront

Abstract

The subaperture stitching technique requires the registration of freeform subapertures into global coordinate frame before stitching in order to compute entire freeform wavefront. A scanning Shack-Hartman Sensor (SHS) utilizes translation stages to scan the freeform surface in XY plane and measure the slope data of various subapertures. The measured slope data is then integrated using weighted cubic spline (WCSLI) based integration method to compute the phase data. The positioning error during scanning causes misalignments between the measured subapertures and their nominal values. The least square based subaperture stitching methods are not capable to minimize lateral misalignment errors of freeform subapertures and therefore degrade the performance of subaperture stitching process. In this work, we have utilized fiducial added planes for correction of angular and rotation misalignments of an extended cubic phase plate. An intrinsic surface feature (ISF) based registration method is used for lateral misalignment corrections. Gaussian curvature is used as an intrinsic pattern which can be defined as one of the fundamental second order geometric properties of a surface. Any shift in the peaks of the Gaussian curvature of reference and measured subaperture corresponds to lateral misalignments in X and Y directions and need to be minimized before registration of subaperture into global frame of reference. After precise registrations, all the subapertures are stitched with consistent overlapping area by using least square fitting method. A numerical validation of the proposed scheme is carried out which demonstrates the effectiveness of the proposed method to improve the subaperture stitching accuracy.