Optical synthetic aperture circle-array optimization based on genetic algorithm

An optimization model of circle array was set up from the basic optical synthetic aperture imaging principle. The circle array was optimized by adopting a genetic algorithm with an improved real coding method coding the location of sub-apertures. The measure function was designed based on maximizing...

Full description

Saved in:
Bibliographic Details
Published inFrontiers of Optoelectronics (Online) Vol. 1; no. 3-4; pp. 268 - 273
Main Authors HE, Yuntao, JIANG, Yuesong, LIU, Guangda
Format Journal Article
LanguageEnglish
Published Heidelberg Higher Education Press 01.12.2008
SP Higher Education Press
Subjects
Online AccessGet full text
ISSN2095-2759
1674-4128
2095-2767
1674-4594
DOI10.1007/s12200-008-0070-9

Cover

More Information
Summary:An optimization model of circle array was set up from the basic optical synthetic aperture imaging principle. The circle array was optimized by adopting a genetic algorithm with an improved real coding method coding the location of sub-apertures. The measure function was designed based on maximizing the distances between u- v coverage dots and minimizing the redundant array. The point spread function, optical transfer function and diffractive imaging were analyzed with the circle array synthetic aperture imaging system. The optimized result of 8 to 16 sub-apertures on a circle array was obtained, and they were compared to the results achieved through simulated annealing algorithm. Using the emulator program, the point spread function was analyzed and contrasted to that of a uniform circle array. Results show that the real coding genetic algorithm can resolve the array optimization well, cost less time and get a better optimization compared with the simulated annealing algorithm.
Bibliography:genetic algorithm
u- v coverage
synthetic aperture
real coding
array optimization
ISSN:2095-2759
1674-4128
2095-2767
1674-4594
DOI:10.1007/s12200-008-0070-9