障碍干扰下的压缩感知电磁成像算法
Compressive sensing electromagnetic imaging algorithm in the presence of obstacle interference
周炽 1杨春夏1
作者信息
- 1. 上海师范大学 信息与机电工程学院,上海 201418
- 折叠
摘要
基于电磁成像模型,针对逆散射问题的病态性和非线性性质,引入压缩感知(CS)中的全变分(TV)算法,旨在减少所需天线数量,并提高电磁成像的图像质量.在玻恩(Born)迭代的基础上,引入全变分压缩感知算法(TV-CS).仿真结果显示:即使目标被障碍物遮挡,该算法也能够在配置较少探测天线的情况下,对目标位置和形状进行准确的重构.
Abstract
Based on the electromagnetic imaging model,the ill-posed and nonlinear nature of the inverse scattering problem was addressed by introducing the total variation(TV)algorithm in compressive sensing(CS)to reduce the required number of antennas and to enhance the image quality of electromagnetic imaging.Building upon the Born iteration,the total variation compressive sensing(TV-CS)algorithm was introduced.Simulation results demonstrated that this algorithm could achieve more accurate reconstruction of target position and shape with fewer deployed antennas,even in scenarios where the target was obscured
关键词
电磁逆散射/压缩感知(CS)/Born迭代/全变分(TV)算法Key words
electromagnetic inverse scattering/compressive sensing(CS)/Born iteration/total variation(TV)algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据