Study On The Key Issues Of The Optical Sparse-Aperture Imaging Systems

Spatial resolution is an important performance index for evaluating space optical remote sensors. In order to achieve the desired increases in spatial resolution, an optical system with a large aperture need to be manufactured. Unfortunately, the primary mirror diameter is limited by material, mass, cost, volume, etc. The optical sparse-aperture imaging system is one of the revolutionary solutions for these problems. The basic theory and some key issues of the optical sparse-aperture imaging systems are studied in this dissertation. Especially, the optimization of aperture configuration and beam combining errors sensing are discussed in detail, and new methods are proposed respectively.The main researched contents are as follows:1. The basic theory of the optical sparse-aperture imaging systems is studied, and simulation experiment is carried out.The basic theory of the optical sparse-aperture imaging systems and typical configurations are described. Point Spread Function (PSF) and Modulation Transfer Function (MTF) of these systems are studied by theoretical analysis and computer simulation. The expressions of the PSF and MTF are achieved, which are related to the aperture configurations. The performance indexes for evaluating the sparse-aperture configurations are illustrated. The MTFs of some typical aperture configurations are analyzed, and the process of imaging simulation based on the simplified model is discussed as well as image recovering for sparse-aperture systems.2. Design and optimization of aperture configuration are studied in detail, and a new method of aperture configuration optimization is proposed, which based on Monte Carlo Inversion.Aperture configuration has a direct effect on MTF for an optical sparse-aperture imaging system. So, design and optimization of aperture configuration is one of the key issues of the optical sparse-aperture imaging systems. The basic principles for the Aperture configuration of an optical sparse-aperture imaging system are studied on the basis of the linear arrays. A new method of aperture configuration optimization is proposed, which based on Monte Carlo Inversion. It can greatly reduce the number of trial aperture models through discrete model space by thick grid and improve optimization speed through random search and systematic search alternately to search model space. The performance of this method is evaluated and analyzed by computer simulation. Some two-dimensional aperture configurations are optimized, and the optimization efficiency is evaluated. The optimality results are agreed with the results of the other literatures. These certify that the aperture model space is discretized reasonably by the new method, and this method has higher optimization efficiency. Finally, a new aperture configuration is analyzed, that is Equilateral Six Sub-Apertures.3. Beam combining errors of the optical sparse-aperture imaging systems are analyzed.In order to achieve phased coherent beam combining, there are three primary beam combining errors needed to be controlled for an optical sparse-aperture imaging system. These beam combining errors are piston errors, tilt errors and pupil mapping errors. They are discussed on the basis of Multiple Telescopes System. The effects of these errors for PSF, MTF and FOV are analyzed in detail by theoretical study and computer simulation.4. The methods for sensing beam combining errors are studied in detail, and a new sensing method is proposed, that is phase diversity wave-front sensing based on SOFM NN.Beam coherent combining is key point of improving spatial resolution by optical sparse-aperture imaging technique. It has significant meaning to research methods for sensing beam combining errors. Because of its characteristics, phase diversity sensing method has greatly potential for development and application. The reasons and present situation of introducing Artificial-Neural-Network into phase diversity sensing method are introduced. In order to improve the speed of PD Wave-front Sensing and reduce the size of training set effectively, a new method based on the combination of phase diversity with neural networks was proposed, which named phase diversity wave-front sensing based on SOFM NN. The simulation of wave-front sensing and closed-loop control for Golay-3 system was implemented on Matlab platform by this method. The simulation results show that beam combining errors can be sensed correctly, and the RMS wave-front errors can be converged less thanλ/14 after 4 iterations. Thus, it is proved that the new sensing method is a good wave-front sensing method in theory. It has a potential value of practical application.5. Some verified experiments are carried out.The experimental verification platform is set up on the basis of the basic theory and simplified model. The experimental contents are as follows: PSF for various aperture configurations, the effects of piston errors for the PSF of a two-aperture system and the performance of the new sensing method for measuring piston errors in one of the Golay-3 apertures. The experimental results verify the correctness of theoretical study and computer simulation as well as the feasibility of the new sensing method.