改进郊狼算法用于直线阵列零陷综合

doi:10.19665/j.issn1001-2400.2021.06.021

摘要/Abstract

摘要：

针对智能优化算法在具有最小旁瓣电平和零陷深度的均匀激励非周期直线阵列零陷综合中存在收敛速度慢及易于陷入局部最优的问题,提出了一种基于改进郊狼算法的直线阵列综合。该算法在郊狼算法的基础上,提出次优个体变异策略和全局最优组内引导策略。在次优个体中引入Hybrid映射扰动,小范围内发生变异,提高种群多样性,扩大搜索范围;构建一种新型的成长方式,提出全局最优组内引导策略,使算法更快地接近全局最优解,提高局部搜索能力并加快收敛速度。仿真结果显示,改进后的郊狼算法较原郊狼算法收敛速度明显加快,与遗传算法、布谷鸟算法、基于生物地理学的优化算法和Taguchi算法相比,所提算法获得了更优的旁瓣电平和零陷深度,证明了算法的有效性和优越性。

关键词: 阵列综合, 旁瓣抑制, 零陷控制, 均匀线阵

Abstract: Aim

ing at the problems in the synthesis of uniformly excited linear arrays with a minimum sidelobe level (SLL) and null steering,a linear array synthesis strategy of the improved coyeto optimization algorithm (ICOA) is proposed.Based on the coyeto optimization algorithm (COA),the suboptimal individual variation strategy and the global optimal intra-group guidance strategy are proposed.Hybrid mapping disturbance is introduced into suboptimal individuals,which causes variation within a small range,improving the population diversity and expanding the search scope.Besides,a new growth mode is constructed and a global optimal intra-group guidance strategy is proposed to make the algorithm approach the global optimal solution faster,enhancing the local search ability and accelerating the convergence speed.Simulation results show that the convergence speed of the ICOA is significantly faster than that of the COA.Compared with the genetic algorithm,cuckoo algorithm,biogeography-based optimization algorithm and Taguchi algorithm,the ICOA obtains better SLL and null steering,which proves the effectiveness and superiority of the proposed algorithm.

Key words: thinned array synthesis, sidelobe suppression, nulls control, uniform linear array

中图分类号:

TN92

国强,李佳莹,王亚妮. 改进郊狼算法用于直线阵列零陷综合[J]. 西安电子科技大学学报, 2021, 48(6): 172-178.

GUO Qiang,LI Jiaying,WANG Yani. Synthesis of linear arrays with sidelobe suppression and null steering using the improved coyeto optimization algorithm[J]. Journal of Xidian University, 2021, 48(6): 172-178.

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性能	ICOA	GA	BBO	CS	COA
最优旁瓣电平/dB	-18.27	-17.39	-17.96	-17.59	-18.15
最差旁瓣电平/dB	-17.95	-16.18	-16.61	-16.34	-17.12
平均旁瓣电平/dB	-18.07	-16.80	-17.29	-17.25	-17.89
方差	0.021	0.176	0.141	0.109	0.081 2

方法	32阵元			20阵元			20阵元
	SLL/dB	NDL/dB	FNBW/(°)	SLL/dB	NDL/dB		SLL/dB	NDL/dB
	SLL/dB	81°	FNBW/(°)	SLL/dB	50°	56.5°	SLL/dB	69.5°	76°
ICOA	-16.71	-168.4	8.4	-14.36	-153.9	-142.0	-12.93	-125.1	-123.6
COA	-16.44	-109.8	8.4	-14.07	-133.7	-138.5	-12.62	-110.8	-105.6
CS^[6]	-15.68	-108.8	8.4	-13.90	-91.84	-111.5	-12.21	-81.00	-88.90
BBO^[7]	-14.69	-109.6	8.4	-13.60	-89.26	-99.87	-11.77	-78.89	-88.90
Taguchi^[8]	-14.68	-78.33	8.6	-14.30	-77.82	-79.51	-12.27	-77.26	-75.22