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Large segmented sparse aperture collimation by curvature sensing.

Qichang An, Xiaoxia Wu, Xudong Lin

|December 31, 2020

Summary

This summary is machine-generated.

This study introduces a cost-effective method for aligning large segmented telescopes using sparse aperture testing and curvature sensing. This technique significantly improves system performance and addresses alignment errors in optical systems.

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Area of Science:

Optical Engineering
Astronomy Instrumentation
Metrology

Background:

Large segmented telescopes require precise alignment for high angular resolution.
Monolithic apertures of equivalent size present significant mass and volume challenges.
Sparse aperture testing offers a cost-effective alternative for alignment and metrology.

Purpose of the Study:

To develop and validate a combined sparse aperture testing and curvature sensing method for fine alignment of segmented telescopes.
To analyze and quantify stitching errors, including tip/tilt/piston and shifting errors.
To improve the traditional alignment methodology by addressing tipping and shifting errors.

Main Methods:

Theoretical and numerical analysis of stitching errors.
Evaluation of errors using normalized point source sensitivity (PSSn).
Utilizing defocused donuts to calculate residual alignment errors during the process.

Main Results:

Demonstrated system performance improvement exceeding 35% through simulations and experiments.
Successfully quantified residual alignment errors using changes in PSSn.
The combined method effectively addresses tipping and shifting errors.

Conclusions:

Sparse aperture testing combined with curvature sensing is an effective and efficient method for aligning large segmented telescopes.
This approach offers a significant improvement over traditional alignment techniques.
The methodology is applicable both in the optics shop and at the observatory.