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...

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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
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ISSN2095-2759
1674-4128
2095-2767
1674-4594
DOI10.1007/s12200-008-0070-9

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Abstract 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.
AbstractList 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.
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.
Author HE, Yuntao
LIU, Guangda
JIANG, Yuesong
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Issue 3-4
Keywords genetic algorithm
coverage
synthetic aperture
real coding
array optimization
Language English
License This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Notes genetic algorithm
u- v coverage
synthetic aperture
real coding
array optimization
OpenAccessLink https://journal.hep.com.cn/foe/EN/10.1007/s12200-008-0070-9
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Snippet 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...
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StartPage 268
SubjectTerms array optimization
Biomedical Engineering and Bioengineering
Electrical Engineering
Engineering
genetic algorithm
Physics
real coding
Research Article
synthetic aperture
u- v coverage
Title Optical synthetic aperture circle-array optimization based on genetic algorithm
URI https://journal.hep.com.cn/foe/EN/10.1007/s12200-008-0070-9
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