Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/163772
Title: Hybrid Genetic Algorithm and Modified Iterative Fourier Transform Algorithm for Large Thinned Array Synthesis
Authors: Can Cui;Wen Tao Li;Xiu Tiao Ye;Xiao Wei Shi
Year: 2017
Publisher: IEEE
Abstract: In this letter, a hybrid algorithm based on the genetic algorithm (GA) and modified iterative Fourier transform (MIFT) technique called HGAMIFT is proposed for large thinned array synthesis. By employing a perturbation mechanism, the MIFT can achieve a better solution in terms of the peak sidelobe level when compared to the iterative Fourier transform technique. Moreover, a control factor to determine the proportion of individuals from GA and MIFT as well as the crossover and mutation rate is introduced to help the HGAMIFT maintain the diversity of population in the early phase while avoiding stagnation in the late phase. Thus, a resulting enhanced search ability and fast convergence velocity can be obtained simultaneously. Several thinned arrays that comprise different array sizes and aperture shapes have been synthesized, which validate the superior performance of the proposed algorithm.
Description: 
URI: http://localhost/handle/Hannan/163772
volume: 16
More Information: 2150,
2154
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7918518.pdf474.37 kBAdobe PDF
Title: Hybrid Genetic Algorithm and Modified Iterative Fourier Transform Algorithm for Large Thinned Array Synthesis
Authors: Can Cui;Wen Tao Li;Xiu Tiao Ye;Xiao Wei Shi
Year: 2017
Publisher: IEEE
Abstract: In this letter, a hybrid algorithm based on the genetic algorithm (GA) and modified iterative Fourier transform (MIFT) technique called HGAMIFT is proposed for large thinned array synthesis. By employing a perturbation mechanism, the MIFT can achieve a better solution in terms of the peak sidelobe level when compared to the iterative Fourier transform technique. Moreover, a control factor to determine the proportion of individuals from GA and MIFT as well as the crossover and mutation rate is introduced to help the HGAMIFT maintain the diversity of population in the early phase while avoiding stagnation in the late phase. Thus, a resulting enhanced search ability and fast convergence velocity can be obtained simultaneously. Several thinned arrays that comprise different array sizes and aperture shapes have been synthesized, which validate the superior performance of the proposed algorithm.
Description: 
URI: http://localhost/handle/Hannan/163772
volume: 16
More Information: 2150,
2154
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7918518.pdf474.37 kBAdobe PDF
Title: Hybrid Genetic Algorithm and Modified Iterative Fourier Transform Algorithm for Large Thinned Array Synthesis
Authors: Can Cui;Wen Tao Li;Xiu Tiao Ye;Xiao Wei Shi
Year: 2017
Publisher: IEEE
Abstract: In this letter, a hybrid algorithm based on the genetic algorithm (GA) and modified iterative Fourier transform (MIFT) technique called HGAMIFT is proposed for large thinned array synthesis. By employing a perturbation mechanism, the MIFT can achieve a better solution in terms of the peak sidelobe level when compared to the iterative Fourier transform technique. Moreover, a control factor to determine the proportion of individuals from GA and MIFT as well as the crossover and mutation rate is introduced to help the HGAMIFT maintain the diversity of population in the early phase while avoiding stagnation in the late phase. Thus, a resulting enhanced search ability and fast convergence velocity can be obtained simultaneously. Several thinned arrays that comprise different array sizes and aperture shapes have been synthesized, which validate the superior performance of the proposed algorithm.
Description: 
URI: http://localhost/handle/Hannan/163772
volume: 16
More Information: 2150,
2154
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7918518.pdf474.37 kBAdobe PDF