Pattern recognition and signal analysis in a Mach-Zehnder type phasing sensor

I. Surdej; H. Lorch; L. Noethe; N. Yaitskova; R. Karban

doi:10.1117/12.734481

24 September 2007 Pattern recognition and signal analysis in a Mach-Zehnder type phasing sensor

I. Surdej, H. Lorch, L. Noethe, N. Yaitskova, R. Karban

Proceedings Volume 6696, Applications of Digital Image Processing XXX; 66960L (2007) https://doi.org/10.1117/12.734481
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

The primary mirror of future Extremely Large Telescopes will be composed of hundreds of individual segments. Misalignments in piston and tip-tilt of such segments must be reduced to a small fraction of the observing wavelength in order not to affect the image quality of these telescopes. In the framework of the Active Phasing Experiment carried out at ESO, new phasing techniques based on the concept of pupil plane detection will be tested. The misalignments of the segments produce amplitude variations at locations on a CCD detector corresponding to the locations of the segment edges. The position of the segment edges on a CCD image must first be determined with pixel accuracy in order to localize the signals which can be analyzed in a second phase with a robust signal analysis algorithm. A method to retrieve the locations of the edges and a phasing algorithm to measure the misalignments between the segments with an accuracy of a few nanometers have been developed. This entire phasing procedure will be presented. The performance of the pattern recognition algorithm will be studied as a function of the number of photons, the amplitude of the segment misalignments and their distribution. Finally, the accuracy achieved under conditions similar to the ones met during observation will be discussed.

Citation Download Citation

I. Surdej, H. Lorch, L. Noethe, N. Yaitskova, and R. Karban "Pattern recognition and signal analysis in a Mach-Zehnder type phasing sensor", Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66960L (24 September 2007); https://doi.org/10.1117/12.734481

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