Research On Improving The Performance Of Liquid Crystal Adaptive Optics Systems

Although the adaptive optics technology has been widely applied in large aperture telescope systems, most of the adaptive optics systems (AOs) have to be working in infrared band, limited by the lack of actuators of traditional deformable mirror (DM) wavefront corrector. However, in visible wave band, not only telescope presents higher resolution, but also most of the celestial objects have higher radiating energy. Hence new type of wavefront corrector with high density of actuators that could satisfy the requirement of large aperture telescopes in visible wave band is the sticking point of next generation AOs. While this is exactly the advantage of novel liquid crystal wavefront corrector (also named as LCOS).Predecessors have solved some of the problems of LCOS, like slow response speed, energy loss due to polarization property and narrow correction wave band due to dispersion. However, up to today, there are still fellowing disadvantages that hinder the application of liquid crystal adaptive optics systems (LCAOS):1) Large computing time delay due to vast complexity in data processing. The pixels of LCOS are dozens of times more than the actuators of DM, this brings huge computation during wavefront reconstruction, causes computing time delay in milliseconds that would evidently limits the correction bandwidth of LCAOS.2) Low precision in the measurement of interaction matrix. Static aberration, random noise and disturbance in LCAOS would impact the precision of interaction matrix measurement, and then affect the performance of LCAOS correction.3) Low accuracy in open loop correction. Because it’s very hard to control the residual error that is impossible to be detected in a open loop structure, which is adopted by LCAOS to reduce the energy loss due to polarization property.In this dissertation, a parallel data processing technology based on multi-CPU and multi-GPU is carried out to solve the problem of vast computational complexity for LCAOS. The two major tasks of data processing in LCAOS is centroid detection and wavefront reconstruction. The centroid detection algorithm is implemented on 16-CPUs because of its relatively low complexity, and the wavefront reconstruction algorithm is implemented on 4-GPUs due to its high complexity, thereby the speed of data processing is dramatically increased:the computing time of centroid detection is reduced from 214us to 27us, with a gain of 7.9 in speed; and the computing time of wavefront reconstruction is reduced from 690us to 90us, with a gain of 7.7 in speed.A novel interaction matrix measurement method based on least square statistics is brought out to improve the precision of interaction matrix measurement. By eliminating the influence of random noise and disturbance during measurement via statistic method, the accuracy of the interaction matrix is improved with a factor of 2, and the power spectrum of the image after correction is enhanced with a gain of nearly 3 at maximum.As to the problem of low accuracy in open loop correction, a open loop adaptive controller is presented with residual error constructed from system transfer function, to remove the error caused by the delay of dynamic response of wavefront sensor and corrector partially. At first, making use of the relationship between phase modulation and light intensity modulation of LCOS, innovatively replace the input of LCAOS from Zernike coefficients to driving voltage of LCOS, so that LCAOS could be simplified from a 35-input 35-output system to a single-input single-out (SISO) system; then the transfer function of the SISO system is identified through subspace system identification, and corroborated that the precision of the system transfer function is 90%, the uniformity of different areas of LCOS and Shack-Hartmann wavefront sensor is identical to 95%, and the time-invariance of the system is less than 7% in two months, hence the acquired system transfer function could accurately describe the liquid crystal adaptive optics system and could be used during controller design as constant function; Finally a open loop correction residual error function is constructed based on the acquired system transfer function, then a first-order controller with parameter adaptively updating during correction is designed, the correction precision of LCAOS is improved by 32%.This dissertation has developed heuristic parallel data processing technology, least square interaction matrix measurement method and open loop adaptive control algorithm, hence notably improves the performance of liquid crystal adaptive optics systems. The results of this dissertation have contributed to the theory and application for liquid crystal adaptive optics systems on a certain extent.