Paper
3 September 2015 State estimation in optical system alignment using monochromatic beam imaging
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Abstract
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joyce Fang and Dmitry Savransky "State estimation in optical system alignment using monochromatic beam imaging", Proc. SPIE 9582, Optical System Alignment, Tolerancing, and Verification IX, 95820F (3 September 2015); https://doi.org/10.1117/12.2186579
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Cited by 1 scholarly publication.
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KEYWORDS
Lenses

Filtering (signal processing)

Control systems

Imaging systems

Optical alignment

Neptunium

Monochromatic aberrations

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