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The use of Adaptive Optics in Extremely Large Telescopes brings newchallenges, one of which is the treatment of Shack-Hartmann Wavefront sensorsimages. When using this type of sensors in conjunction with laser guide starsfor sampling the pupil of telescopes with 30+ m in diameter, it is necessary tocompute the centroid of elongated spots, whose elongation angle and aspectratio are changing across the telescope pupil. Existing techniques such asMatched Filter have been considered as the best technique to compute thecentroid of elongated spots, however they are not good at coping with theeffect of a variation in the Sodium profile. In this work we propose a newtechnique using artificial neural networks, which take advantage of the neuralnetwork's ability to cope with changing conditions, outperforming existingtechniques in this context. We have developed comprehensive simulations toexplore this technique and compare it with existing algorithms.

Artificial neural networks for centroiding elongated spots in Shack-Hartmann wavefront sensors