Optimization Of Multi-objective Simulated Annealing Array For Optical Sparse Aperture

Imaging technology with excellent spatial resolution plays an important role in the field of earth survey and space exploration.Generally,images with excellent resolution can be obtained by extending the focal length and enlarging the aperture.Considering factors such as manufacturing difficulty and material cost,relevant researchers began to explore new directions to solve the above problems.One of the effective schemes is optical sparse aperture imaging system.The critical technology in this scheme is the optimization of pupil structure.This paper will start with the basic theory of sparse aperture imaging technology and optimize the sparse aperture array by using simulated annealing algorithm.Main research contents are as follows:Firstly,the research background of sparse aperture optical system and the latest research situation at home and abroad are summarized.Secondly,the fundamental principle of sparse aperture imaging technology is expounded,the expression of modulation transfer function(MTF)in optical sparse aperture imaging system is introduced,and its significant characteristic indexes and physical meanings are analyzed.The basic ideas and specific operation steps of pupil structure optimization are described in detail.Then,the structural optimization of multi-target aperture array is studied emphatically.On the basis of the characteristics of sparse aperture imaging system MTF,the objective function of spectrum optimization of sparse aperture array in multiple directions is designed as expected.The degraded Golay6 and Golay9 arrays are taken as the initial arrays,and the arrays are optimized after being constrained from two vertical directions and three directions respectively.The simulation operation is realized in MATLAB,and the original effect is achieved.The results show that the simulated annealing algorithm can make the middle and high frequency bands of MTF more smooth and steady and obviously improve the actual cut-off frequency of imaging array.For example,when the filling factor is F=0.115,compared with Golay6 aperture array,the average correction factor of the optimized aperture array constrained by two vertical directions reaches 8.61%;When the filling factor is F=0.04,compared with Golay9 aperture array,the average correction factor of the optimized aperture array constrained by two vertical directions reaches 13.83%.On the other hand,the radial multi-mirror array is characterized by a large number of subapertures,so the evaluation index based on baseline length statistics is selected.According to the principle of uniformity of baseline length distribution,the corresponding objective function is designed,and the degraded II-312 radial multi-mirror array was taken as the initial array,the results obtained by MATLAB optimization are in line with the expected assumptions.Using simulated annealing algorithm can ameliorate the equidistribution of baseline length.When the filling factor is F=0.14,the average correction factor of the optimized aperture array is 4.02%,compared with the Ⅱ-312 radial multi-mirror aperture array.