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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Current tracking and adaptive optics techniques cannot compensate for fastmoving extended objects, which is important for ground-based telescopes providing space situational awareness. To fill this need, a vector-projection maximum-likelihood wave-front sensing algorithm development and testing follows for this application. A derivation and simplification of the Cramer-Rao Lower Bound for wave-front sensing using a laser guide star bounds the performance of these systems and guides implementation of a vastly optimized maximum-likelihood search algorithm. A complete analysis of the bias, mean square error, and variance of the algorithm demonstrates exceptional performance of the new sensor. A proof of concept implementation shows feasibility of deployment in modern adaptive optics systems. The vector-projection maximum-likelihood sensor satisfies the need for tracking and wave-front sensing of extended objects using current adaptive optics hardware designs.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Current tracking and adaptive optics techniques cannot compensate for fastmoving extended objects, which is important for ground-based telescopes providing space situational awareness. To fill this need, a vector-projection maximum-likelihood wave-front sensing algorithm development and testing follows for this application. A derivation and simplification of the Cramer-Rao Lower Bound for wave-front sensing using a laser guide star bounds the performance of these systems and guides implementation of a vastly optimized maximum-likelihood search algorithm. A complete analysis of the bias, mean square error, and variance of the algorithm demonstrates exceptional performance of the new sensor. A proof of concept implementation shows feasibility of deployment in modern adaptive optics systems. The vector-projection maximum-likelihood sensor satisfies the need for tracking and wave-front sensing of extended objects using current adaptive optics hardware designs.