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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:LONG Wei-jun,BEN De,ZHANG Gong.Pattern synthesis optimization of 3-D ODAR based on improved GA using LSFE method[J].Journal of Harbin Institute Of Technology(New Series),2011,18(1):96-100.DOI:10.11916/j.issn.1005-9113.2011.01.018.
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Pattern synthesis optimization of 3-D ODAR based on improved GA using LSFE method
Author NameAffiliation
LONG Wei-jun College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China 
BEN De College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China 
BAKHSHI ASIM D Computer Engineering,University of Engineering and Technology,Lahore 540000,Pakistan 
ZHANG Gong College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China 
Abstract:
Pattern synthesis in 3-D opportunistic digital array radar(ODAR) becomes complex when a multitude of antennas are considered to be randomly distributed in a three dimensional space.In order to obtain an optimal pattern,several freedoms must be constrained.A new pattern synthesis approach based on the improved genetic algorithm(GA) using the least square fitness estimation(LSFE) method is proposed.Parameters optimized by this method include antenna locations,stimulus states and phase weights.The new algorithm demonstrates that the fitness variation tendency of GA can be effectively predicted after several "eras" by the LSFE method.It is shown that by comparing the variation of LSFE curve slope,the GA operator can be adaptively modified to avoid premature convergence of the algorithm.The validity of the algorithm is verified using computer implementation.
Key words:  antenna radiation patterns  genetic algorithm(GA)  opportunistic digital array radar(ODAR)  pattern synthesis  the least square fitness estimation(LSFE)
DOI:10.11916/j.issn.1005-9113.2011.01.018
Clc Number:TN957.2
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