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

TL;DR

This paper presents a novel method for automated optical system alignment using only focal-plane images, PCA, and Kalman filtering, eliminating the need for dedicated wavefront sensors.

Contribution

It introduces a self-aligning approach for reconfigurable optical systems that relies solely on focal-plane images and advanced filtering techniques, enhancing flexibility and efficiency.

Findings

Successful simulation of system alignment using the proposed method

Experimental validation demonstrating effective real-time alignment

Improved flexibility without dedicated wavefront sensors

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 eight degrees of freedom. Images are simulated given misalignment parameters using ZEMAX software. We perform a principal component analysis (PCA) on the simulated dataset to obtain Karhunen-Lo\`eve (KL) 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 both simulated and experimental results of the full system in operation.