论文:2017,Vol:35,Issue(5):780-785
引用本文:
孙翠珍, 丁君, 兰建锋, 郭陈江, 袁建涛. 改进的引力搜索算法用于阵列天线方向图综合[J]. 西北工业大学学报
Sun Cuizhen, Ding Jun, Lan Jianfeng, Guo Chenjiang, Yuan Jiantao. Application of the Improved Gravitational Search Algorithm for the Pattern Synthesis of Array Antennas[J]. Northwestern polytechnical university

改进的引力搜索算法用于阵列天线方向图综合
孙翠珍1,2, 丁君1, 兰建锋1, 郭陈江1, 袁建涛1
1. 西北工业大学 电子信息学院, 陕西 西安 710072;
2. 西安科技大学 通信与信息工程学院, 陕西 西安 710054
摘要:
针对基本引力搜索算法在处理复杂的阵列天线综合问题时,存在早熟收敛和收敛速度慢的缺陷,提出了一种混合引力搜索算法。首先将精英粒子保护算法及后进粒子微扰算法嵌入到基本的引力搜索算法中,延长了粒子的存活时间,扩大了粒子邻域的搜索范围,保护了种群的多样性,较大程度上改善了算法过早收敛的问题;其次重新定义了惯性质量调节系数q,使种群中粒子惯性质量的差距增大,算法能够快速有效地收敛于问题的最优解,从而改善了全局收敛性与局部收敛性的平衡。将该算法用于20元阵列天线方向图综合中,仿真结果表明,与基本的引力搜索算法以及同类智能优化算法相比,改进后的算法在计算精度和收敛速度,及种群多样性方面均有显著改善。
关键词:    引力搜索算法    精英粒子    后进粒子    惯性质量调节系数    方向图综合   
Application of the Improved Gravitational Search Algorithm for the Pattern Synthesis of Array Antennas
Sun Cuizhen1,2, Ding Jun1, Lan Jianfeng1, Guo Chenjiang1, Yuan Jiantao1
1. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710054, China
Abstract:
In order to overcome the problems of the premature convergence and the slow convergence speed caused by the gravitational search algorithm (GSA) in the complex pattern synthesis of array antennas, an improved gravitational search algorithm——the hybrid gravitational search algorithm (HGSA) is presented. By extending the survival time of the elite particles and the backward particles appropriately, the diversity of the population is protected, so the problem of premature convergence of the GSA is solved; To balance the global and local searching capabilities, make the algorithm converge to the optimal solution quickly and effectively, the size of the inertia mass coefficient q is adjusted. The synthesis of the 20 elements array antenna with two examples based on the HGSA, GSA, GA, PSO are simulated. The experimental results have demonstrated that the HGSA can achieve better accuracy and faster convergence rate compared with other three algorithms.
Key words:    gravitational search algorithm    elite particles    backward particles    inertia mass coefficient    pattern synthesis   
收稿日期: 2017-02-20     修回日期:
DOI:
基金项目: 国家自然科学基金青年科学基金(61302133)、西安市科技计划项目(CXY1440(4))及西安科技大学教学方法与教学手段改革项目(ZX16032)资助
通讯作者:     Email:
作者简介: 孙翠珍(1981-),女,西北工业大学博士研究生,主要从事微波技术与天线算法研究。
相关功能
PDF(1167KB) Free
打印本文
把本文推荐给朋友
作者相关文章
孙翠珍  在本刊中的所有文章
丁君  在本刊中的所有文章
兰建锋  在本刊中的所有文章
郭陈江  在本刊中的所有文章
袁建涛  在本刊中的所有文章

参考文献:
[1] 苟艳妮,王英民,王奇. 利用模拟退火算法的多基地浮标定位研究[J]. 西北工业大学学报,2013,31(4):607-613 Gou Yanni, Wang Yingmin, Wang Qi. Applying Simulated Annealing Algorithm to Locating Multistatic Bouy[J]. Journal of Northwestern Polytechnical University,2013,31(4):607-613(in Chinese)
[2] Oliveri G, Massa A. Genetic Algorithm(GA)-Enhanced Almost Difference Set(ADS)-Based Approach for Array Thinning[J]. IET Microwaves Antennas & Propagation, 2011, 5(3):305-315
[3] Ishaque K, Salam Z, Amjad M, et al. An Improved Particle Swarm Optimization (PSO)-Based MPPT for Pv with Reduced Steady-State Oscillation[J]. IEEE Trans on Power Electronics, 2012, 27(8):3627-3638
[4] 高晓光,邸若海,郭志高. 基于改进粒子群优化算法的贝叶斯网络结构学习[J]. 西北工业大学学报,2014,32(5):749-755 Gao Xiaoguang, Di Ruohai, Guo Zhigao. Bayesian Network Structure Learning Based on Improved Particle Swarm Optimization[J]. Journal of Northwestern Polytechnical University, 2014,32(5):749-755(in Chinese)
[5] Esmat R, Hossein N, Saeid S. GSA:A Gravitational Search Algorithm[J]. Information Sciences, 2009, 179(13):2232-2248
[6] Hamed N, Hamid M. A New Algorithm for Data Clustering Based on Gravitational Search Algorithm and Genetic Operators[C]//International Symposium on Artificial Intelligence and Signal Processing, 2015:222-227
[7] RejinaParvin J, Vasanthanayaki C. Particle Swarm Optimization-Based Clustering by Preventing Residual Nodes in Wireless Sensor Networks[J]. IEEE Sensors Journal, 2015, 15(8):4264-4274
[8] Zhang E Z, Wu Y F, Chen Q W. A Hybrid Multi-Objective PSOGSA Approach for Environmental/Economic Dispatch[C]//IEEE Conference on Industrial Electronics and Applications, 2015:455-460
[9] Gouthamkumar N, Veena S, Ram N. Application of Non-Dominated Sorting Gravitational Search Algorithm with Disruption Operator for Stochastic Multiobjective Short Term Hydrothermal Scheduling[J]. IET Generation, Transmission & Distribution, 2016,10(4):862-872
[10] Arnab G, Subrata B, Mrinal K S, Priyanka D. Design and Implementation of Type-Ⅱ and Type-Ⅲ Controller for DC-DC Switched-Mode Boost Converter by Using K-Factor Approach and Optimisation Techniques[J]. IET Power Electronics, 2016, 9(5):938-950
[11] Zahid H M Iqbal, Ali Shafique. A Hybrid Evolutionary Algorithm for Economic Load Dispatch Proble Considering Transmission Losses and Various Operational Constraints[C]//International Conference on Intelligent Systems Engineering, 2016:202-209
[12] 刘燕,焦永昌,张亚明,等. 基于分解的多目标入侵杂草算法用于阵列天线方向图综合[J]. 西北工业大学学报,2014,32(6):981-986 Liu Yan, Jiao Yongchang, Zhang Yaming, et al. Pattern Synthesis of Array Antennas Using Multi-Objective Invasive Weed Optimization Based on Decomposition[J]. Journal of Northwestern Polytechnical University,2014,32(6):981-986(in Chinese)