Automated alignment of a reconfigurable optical system using focal-plane sensing and Kalman filtering

Abstract

Automation of alignment tasks can provide improved efficiency and greatly increase the flexibility of an optical system. Current optical systems with automated alignment capabilities are typically designed to include a dedicated wavefront sensor. Here, we demonstrate a self-aligning method for a reconfigurable system using only focal plane images. We define a two lens optical system with 8 degrees of freedom. Images are simulated given misalignment parameters using ZEMAX software. We perform a principal component analysis on the simulated data set to obtain Karhunen-Loève modes, which form the basis set whose weights are the system measurements. A model function, which maps the state to the measurement, is learned using nonlinear least-squares fitting and serves as the measurement function for the nonlinear estimator (extended and unscented Kalman filters) used to calculate control inputs to align the system. We present and discuss simulated and experimental results of the full system in operation.