scholarly journals Structure optimization design of a thin-film diffraction imaging system based on the Kriging model and the improved particle swarm optimization algorithm

2021 ◽  
Vol 12 (2) ◽  
pp. 875-889
Author(s):  
Yitian Wang ◽  
Liu Zhang ◽  
Huanyu Zhao ◽  
Fan Zhang

Abstract. A thin-film diffraction imaging system is a type of space telescope imaging system with high resolution and loose surface tolerance often used in various fields, such as ground observation and military reconnaissance. However, because this system is a large and flexible multi-body structure, it can produce flexural vibration easily during the orbit operation, which has a serious effect on the attitude stability of the system and results in low pointing accuracy. Therefore, this study proposes an optimization method based on the Kriging model and the improved particle swarm optimization algorithm to improve the stability and optimize the structure of the entire system. Results showed the area–mass ratio of the thin-film diffraction imaging system decreased by 9.874 %, the first-order natural frequency increased by 23.789 %, and the attitude stability of the thin-film diffraction imaging system improved.

2014 ◽  
Vol 599-601 ◽  
pp. 1453-1456
Author(s):  
Ju Wang ◽  
Yin Liu ◽  
Wei Juan Zhang ◽  
Kun Li

The reconstruction algorithm has a hot research in compressed sensing. Matching pursuit algorithm has a huge computational task, when particle swarm optimization has been put forth to find the best atom, but it due to the easy convergence to local minima, so the paper proposed a algorithm ,which based on improved particle swarm optimization. The algorithm referred above combines K-mean and particle swarm optimization algorithm. The algorithm not only effectively prevents the premature convergence, but also improves the K-mean’s local. These findings indicated that the algorithm overcomes premature convergence of particle swarm optimization, and improves the quality of image reconstruction.


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