Browsing by Author "Osborn, James"

Now showing 1 - 5 of 5
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    An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment
    (MDPI, 2012) de Cos Juez, Francisco J.; Sanchez Lasheras, Fernando; Roqueni, Nieves; Osborn, James
    In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A).
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    Atmospheric turbulence profiling using multiple laser star wavefront sensors
    (2012) Cortés Carvallo, Ángela Johanna; Benoit, Neichel; Guesalaga Meissner, Andrés; Osborn, James; Rigaut, Francois; Guzmán Carmine, Christian Dani
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    Comparison of vibration mitigation controllers for adaptive optics systems
    (OPTICAL SOC AMER, 2012) Guesalaga, Andres; Neichel, Benoit; Rigaut, Francois; Osborn, James; Guzman, Dani
    Vibrations are detrimental to the performance of modern adaptive optics (AO) systems. In this paper, we describe new methods tested to mitigate the vibrations encountered in some of the instruments of the Gemini South telescope. By implementing a spectral analysis of the slope measurements from several wavefront sensors and an imager, we can determine the frequencies and magnitude of these vibrations. We found a persistent vibration at 55 Hz with others occurring occasionally at 14 and 100 Hz. Two types of AO controllers were designed and implemented, Kalman and H-infinity, in the multiconjugate AO tip-tilt loop. The first results show a similar performance for these advanced controllers and a clear improvement in vibration rejection and overall performance over the classical integrator scheme. It is shown that the reduction in the standard deviation of the residual slopes (as measured by wavefront sensors) is highly dependent on turbulence, wind speed, and vibration conditions, ranging-in terms of slopes RMS value-from an almost negligible reduction for high speed wind to a factor of 5 for a combination of low wind and strong vibrations. (c) 2012 Optical Society of America
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    Using artificial neural networks for open-loop tomography
    (OPTICAL SOC AMER, 2012) Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, Jesus
    Modern adaptive optics (AO) systems for large telescopes require tomographic techniques to reconstruct the phase aberrations induced by the turbulent atmosphere along a line of sight to a target which is angularly separated from the guide sources that are used to sample the atmosphere. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. We compare our ANN method with a standard least squares type matrix multiplication method and to the learn and apply method developed for the CANARY MOAO instrument. The ANN is trained with a large range of possible turbulent layer positions and therefore does not require any input of the optical turbulence profile. It is therefore less susceptible to changing conditions than some existing methods. We also exploit the non-linear response of the ANN to make it more robust to noisy centroid measurements than other linear techniques. (C) 2012 Optical Society of America