高技术通讯（英文版）2006，Vol.12Issue(3)：283-287,5.
Composite multiobjective optimization beamforming based on genetic algorithms
Composite multiobjective optimization beamforming based on genetic algorithms
摘要
Abstract
All thc parameters of beamforming are usually optimized simultaneously in implementing the optimization of antenna array pattern with multiple objectives and parameters by genetic algorithms (GAs).Firstly, this paper analyzes the performance of fitness functions of previous algorithms. It shows that original algorithms make the fitness functions too complex leading to large amount of calculation, and also the selection of the weight of parameters very sensitive due to many parameters optimized simultaneously. This paper proposes a kind of algorithm of composite beamforming, which detaches the antenna array into two parts corresponding to optimization of different objective parameters respectively. New algorithm substitutes the previous complex fitness function with two simpler functions. Both theoretical analysis and simulation results show that this method simplifies the selection of weighting parameters and reduces the complexity of calculation. Furthermore, the algorithm has better performance in lowering side lobe and interferences in comparison with conventional algorithms of beamforming in the case of slightly widening the main lobe.关键词
genetic algorithms/composite beamforming/fitness functionKey words
genetic algorithms/composite beamforming/fitness function分类
数理科学引用本文复制引用
Shi Jing,Meng Weixiao,Zhang Naitong,Wang Zheng..Composite multiobjective optimization beamforming based on genetic algorithms[J].高技术通讯（英文版）,2006,12(3):283-287,5.基金项目
Supported by the National Natural Science Foundation of China (No. 60302020). （No. 60302020）
