DocumentCode :
3025129
Title :
Application of multi-population improved cultural genetic algorithm using fuzzy mathematics in synthesis of array radar antenna
Author :
Weiqiane Miao ; Yuming Lu
Author_Institution :
Sch. of Inf. & Eng., Nanchang Hangkong Univ., Nanchang, China
fYear :
2013
fDate :
20-22 Dec. 2013
Firstpage :
1618
Lastpage :
1621
Abstract :
In order to address the optimization problem of array radar antenna and obtain the optimal antenna pattern, a novel hybrid genetic algorithm is proposed. The new algorithm introduces the theory of fuzzy mathematics into acceptance function, update function and influence function of cultural algorithm. Based on multi-population genetic algorithm (MPGA), the novel hybrid algorithm suppresses the peak side lobe level to -17.43908dB through optimizing the phase of array radar antenna. Comparing with the simulation results of cultural genetic algorithm (CGA) [1] and improved cultural genetic algorithm (ICGA), multi-population improved cultural genetic algorithm (MICGA) has the strongest performance of global search and local search, and it can search the global optimum. Besides, the convergence probability of MICGA is the highest and reaches 90%. Thus MICGA has a great prospect in the optimization design of array radar antenna.
Keywords :
antenna arrays; fuzzy set theory; genetic algorithms; radar antennas; MICGA; acceptance function; array radar antenna synthesis; fuzzy mathematics; fuzzy mathematics theory; hybrid genetic algorithm; multipopulation improved cultural genetic algorithm; optimal antenna pattern; optimization design; optimization problem; peak side lobe level; update function; Computers; Conferences; Mechatronics; antenna pattern; array radar antenna; cultural genetic algorithm; fuzzy mathematics; multi-population genetic algorithm; peak side lobe level;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location :
Shengyang
Print_ISBN :
978-1-4799-2564-3
Type :
conf
DOI :
10.1109/MEC.2013.6885319
Filename :
6885319
Link To Document :
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