Paper
3 September 2015 Alignment performance comparison between MFR and MDCO for a TMA optical system
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Abstract
In this study, we performed alignment state estimation simulations and compared the performance of two Computer Aided Alignment (hereafter CAA) algorithms i.e. ‘Merit Function Regression (MFR)’ and ‘Multiple Design Configuration Optimization (MDCO)’ for a TMA optical system. The former minimizes the merit function using multi-field wavefront error measurements from single configuration, while the latter minimizes the merit function using single-field measured wavefront error from multiple configurations. The optical system used is an unobscured three-mirror anastigmat (TMA) optical system of 70mm in diameter, and F/5.0. It is designed for an unmanned aerial vehicle for coastal water remote sensing. The TMA consists of two aspherical mirrors, a spherical mirror and a flat folding mirror. Based on the sensitivity analysis, we set the tilt x, y of tertiary mirror as a compensator, and not considered decenter of tertiary mirror because of its spherical characteristic. For the simulation, we introduced Gaussian distribution of initial misalignment to M3. It has the mean value of zero and standard deviation of 0.5 mrad. The initial simulation result of alignment state estimation shows that both algorithms can meet the alignment requirement, λ/10 RMS WFE at 633nm. However, when we includes measurement noise, the simulation result of MFR shows greater standard deviation in RMS WFE than that of MDCO. As for the measurement, the MDCO requires single on-axis field while the MFR requires multiple fields, we concluded that the MDCO is more practical method to align the off-axis TMA optics than MFR.
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Hyukmo Kang, Eunsong Oh, and Sug-Whan Kim "Alignment performance comparison between MFR and MDCO for a TMA optical system", Proc. SPIE 9582, Optical System Alignment, Tolerancing, and Verification IX, 95820G (3 September 2015); https://doi.org/10.1117/12.2188244
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KEYWORDS
Mirrors

Optical alignment

Monte Carlo methods

Wavefronts

Computer simulations

Detection and tracking algorithms

Remote sensing

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