Sub-array partition method based on particle swarm optimisation for large aperture phased array radar

被引：1

作者：

Chen, Xiaoyan ^{[1
,2
]}

Sun, Yuze ^{[3
]}

Xu, Feng ^{[1
,2
]}

Yang, Xiaopeng ^{[1
,2
]}

机构：

[1] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China

[2] Beijing Inst Technol, Minist Educ, Key Lab Elect & Informat Technol Satellite Nav, Beijing 100081, Peoples R China

[3] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

来源：

JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 19期

基金：

中国国家自然科学基金;

关键词：

phased array radar; particle swarm optimisation; radar signal processing; radar antennas; linear antenna arrays; hardware cost; system complexity; multiple performance parameters optimisation method; multiobjective optimisation problem; single-objective problem; signal processing performances; linear array; large array antennas; subarray partition method; dynamic inertia weights; learning factors; large aperture phased array radar; DESIGN;

D O I：

10.1049/joe.2019.0278

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to reduce hardware cost and system complexity, sub-array partition is necessary for large array antennas. Traditional sub-array partition methods are mainly aiming at the single performance optimisation of beampattern. Therefore, this study proposes a multiple performance parameters optimisation method based on particle swarm optimisation (PSO). In the proposed method, the multi-objective optimisation problem is converted into a single-objective problem, and then dynamic inertia weights and learning factors are used in the algorithm. Based on the proposed method, the signal processing performances can be improved compared with the traditional methods. Through the simulation of the division of the linear array, the effectiveness of the proposed method is verified.

引用

页码：6318 / 6321

页数：4