中国科学院大学学报2025，Vol.42Issue(3)：361-370,10.DOI:10.7523/j.ucas.2023.056
一种基于粒子群算法的星载斜视滑动聚束SAR扫描策略优化方法
A Scanning strategy optimizing method for spaceborne squint sliding spotlight SAR based on particle swarm optimization
摘要
Abstract
In view of the significant spatial variance in the azimuth resolution of traditional spaceborne sliding spotlight SAR,this paper proposes a scanning strategy optimizing method for spaceborne squint sliding spotlight SAR based on particle swarm optimization.The proposed method can basically eliminate the spatial variance of azimuth resolution in SAR images and improve the accuracy of localization and identification when SAR images are used for target identification.Considering that traditional particle swarm optimization is prone to fall into local optimum when optimizing the scanning strategy,this paper proposes an improved particle swarm optimization in which a parameterized model of the sliding factor,whose parameters are solved using particle swarm optimization,is established and a neighborhood search algorithm is integrated so that the ability of the algorithm to reach the optimum is enhanced.Simulation results validate the effectiveness of the proposed method.关键词
合成孔径雷达/方位分辨率/波束扫描策略/粒子群算法Key words
synthetic aperture radar/azimuth resolution/beam scanning strategy/particle swarm optimization分类
电子信息工程引用本文复制引用
龚力维,李飞,韩晓东,王伟..一种基于粒子群算法的星载斜视滑动聚束SAR扫描策略优化方法[J].中国科学院大学学报,2025,42(3):361-370,10.基金项目
国家自然科学基金(61971401)资助 （61971401）
