Automated alignment of optical systems saves the time and energy needed for manual alignment and is required in cases where manual intervention is impossible. This research discusses the state estimation of the misalignment of a reimaging system using a focal plane sensor. We control two moving lenses to achieve high precision alignments by feeding back state estimates calculated from images from a CCD camera. We perform a Principal Component Analysis (PCA) on a simulated data set. The monochromatic images are decoupled into Karhunen- Loève (KL) modes, which are used as the measurement in state estimation. An Extended Kalman filter (EKF) is used to estimate the misalignment of the optical components, and we describe a closed-loop control system with monochromatic beam to demonstrate the performance of the state estimation process. The state and measurement residuals converge with the Kalman observer. The automated alignment technique can be extended to reconfigurable systems with multiple lenses and other optical components.
An automated alignment optical system will greatly simplify alignment tasks, increase the flexibility and utility of reconfigurable optical systems, and allow for the quick and efficient set up distributed optical systems. In this work, we demonstrate automated alignment of a tilted and decentered focal lens using only focal plane imaging by exploiting the aberration effects caused by the misalignment. A Gaussian beam is passed through the lens with 4 degrees of freedom and onto a science camera. The deformation of the spot image is analyzed to determine the tilt and shift misalignments on the lens. Corrections based on these measurements are applied in closed loop to align the system. We discuss various techniques for mitigating measurement errors, characterizing the system and operating the control loop and present results from the experiment.