Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new...Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new form of optimization problems.The new optimization formulation has two differences from the common ones.One is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the designed.This difference is beneficial to decrease complexity in some sense.The second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation parameters.This difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are validated.The results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.展开更多
基金Major Project for New Generation of AI under Grant 2018AAA0100400in part by Scientific Research Fund of Hunan Provincial Education Department of China under Grant 21A0350,21C0439+4 种基金in part by the National Natural Science Foundation of China under Grant 61673355in part by the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)under Grant CUGGC02in part by the Hubei Provincial Natural Science Foundation of China under Grant 2015CFA010in part by the high-performance computing platform of the China University of Geosciencesin part by the 111 projectunder Grant B17040.
文摘Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new form of optimization problems.The new optimization formulation has two differences from the common ones.One is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the designed.This difference is beneficial to decrease complexity in some sense.The second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation parameters.This difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are validated.The results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.
