基于改进交叉熵算法多目标不等间距阵列综合

上海交通大学学报（自然版） ›› 2014, Vol. 48 ›› Issue (03): 372-376.

• 无线电电子学、电信技术 • 上一篇下一篇

基于改进交叉熵算法多目标不等间距阵列综合

边莉，车向前，张少卿

(黑龙江科技大学电子与信息工程学院，哈尔滨 150022)

收稿日期:2013-03-26 出版日期:2014-03-28 发布日期:2014-03-28
基金资助:
黑龙江省青年科学基金（QC2010023），黑龙江省普通高等学校青年学术骨干支持计划（1251G055），黑龙江科技大学优秀青年才俊计划资助

Multi-objective Unequally-Spaced Array Synthesis Based on Modified Cross Entropy Algorithm

BIAN Li,CHE Xiangqian,ZHANG Shaoqing

(School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China)

Received:2013-03-26 Online:2014-03-28 Published:2014-03-28

摘要/Abstract

摘要：

将模糊C均值聚类算法与传统交叉算法相结合，提出改进交叉熵算法.利用该算法成功完成阵元个数分别为6、8、10、12不等间距阵列综合，解决了不等间距阵列综合中峰值旁瓣电平和波束宽度的多目标优化问题，得到了对应情况下不等间距阵列的峰值旁瓣电平和波束宽度的平衡曲线.优化结果表明，给定波束宽度，阵元个数相同的不等间距阵列的峰值旁瓣电平比均匀阵列下降近30%.在均匀阵列超出截止间距时，可以更加有效准确地找寻峰值旁瓣和波束宽度的折中点.

关键词: 阵列综合, 不等间距阵列, 改进交叉熵算法

Abstract:

The modified cross entropy algorithm and the program flow were proposed based on the combination of fuzzy C mean clustering algorithm and traditional cross entropy algorithm. This algorithm was successfully used in unequallyspaced arrays synthesis, whose number of array element are respectively 6, 8, 10, and 12, and solved the multiobjective optimization problems of the peak sidelobe level and beam width in the field of unequallyspaced array synthesis. In the corresponding cases, the balance curves to peak sidelobe level and beam width of unequallyspaced arrays were proposed.Optimization shows that, given the beam width and the number of unequallyspaced array elements, the peak sidelobe level of unequallyspaced array was decreased by nearly 30% compared with equallyspaced array. In the uniform array beyond the cutoff distance, the algorithm more efficiently and accurately found tradeoff to peak sidelobe and beamwidth.

Key words: array synthesis, unequally-spaced array, modified cross entropy algorithm

中图分类号:

TN 821

边莉，车向前，张少卿. 基于改进交叉熵算法多目标不等间距阵列综合[J]. 上海交通大学学报（自然版）, 2014, 48(03): 372-376.

BIAN Li,CHE Xiangqian,ZHANG Shaoqing. Multi-objective Unequally-Spaced Array Synthesis Based on Modified Cross Entropy Algorithm[J]. Journal of Shanghai Jiaotong University, 2014, 48(03): 372-376.

参考文献

［1］Pham M T, Zhang D H.Multiguider and crosssearching approach in multiobjective particle swarm optimization for electromagnetic problems［J］ . IEEE Transactions on Magnetics, 2012, 48(2): 539 542.

［2］Deb K. Multiobjective optimization using evolutionary algorithms ［M］. Chichester, U K: Wiley, 2001.

［3］Jain H, Deb K. An improved adaptive approach for elitist nondominated sorting Genetic Algorithm for manyobjective optimization［C］∥Proceedings of 7th International Conference, EMO 2013. Sheffield, U K: Springer Berlin Heidelberg, 2013: 307321.

［4］Jayasinghe J W, Anguera J, Uduwawala D N. A highdirectivity microstrip patch antenna design by using genetic algorithm optimization ［J］. Progress in Electromagnetics Research C, 2013, 37(5): 131144.

［5］Oliveri G, Massa A.Genetic algorithm (GA)enhanced almost difference set (ADS)based approach for array thinning ［J］. IET Microwaves, Antannas & Propagation, 2011, 5(3): 305315.

［6］Chan C Y, Goggans P M. Using bayesian inference for linear antenna array design ［J］. IEEE Transactions on Antennas and Propagation, 2011, 59(9):32113217.

［7］Lin C, Qing A, Feng Q. Synthesis of unequally spaced antenna arrays by using differential evolution ［J］. Antennas and Propagation, IEEE Transactions on, 2010, 58(8): 25532561.

［8］Behera A K, Ahmad A, Mandal S K, et al. Synthesis of cosecant squared pattern in linear antenna arrays using differential evolution［C］ ∥Information & Communication Technologies (ICT), 2013 IEEE Conference on. JeJu Island, Korea: IEEE, 2013: 10251028.

［9］Goudos S K, Moysia dou V, Samaras T, et al. Application of a comprehensive learning particle swarm optimizer to unequally spaced linear array synthesis with sidelobe level suppression and null control［J］. IEEE Antennas and Wireless Propagation Letters, 2010, 9(3): 125129.

［10］Rubinstein R Y. Optimization of computer simulation models with rare events ［J］. European Journal of Operational Research, 1997, 99(1): 89112.

［11］Duda R, Hart P. Pattern classification and scene analysis ［M］.New York: Wiley, 1973: 2326.

［12］Kroese D P. The crossentropy method: A unified approach to combinatorial optimization, MonteCarlo simulation, and machine learning ［M］. New York: Springer, 2011: 4557.

［13］Panduro M A, Brizuela C A, Covarrubias D, et al. A tradeoff curve computation for linear antenna arrays using an evolutionary multiobjective approach ［J］. Soft Computing-A Fusion of Foundations, Methodologies and Applications, 2006, 10(2): 125131.

［14］Panduro M A, Covarrubias D H, Brizuela C A, et al. A multiobjective approach in the linear antenna array design ［J］. AEUInternational Journal of Electronics and Communications, 2005, 59(4): 205212.

基于改进交叉熵算法多目标不等间距阵列综合

Multi-objective Unequally-Spaced Array Synthesis Based on Modified Cross Entropy Algorithm

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价