雷达科学与技术2018，Vol.16Issue(1)：37-42,6.DOI:10.3969/j.issn.1672-2337.2018.01.006
基于优化最小化框架的墙体成像算法
A Wall Imaging Algorithm Based on Majorization-Minimization Framework
摘要
Abstract
Due to the underutilization of physical properties of the wall,the existing sparse imaging algorithms have some problems in through-wall radar building layout imaging.For instance,the imaging of wall has obscure contour and discontinuous edges,and the process of imaging is very time consuming.This paper proposes a wall imaging algorithm based on majorization-minimization framework.Firstly,the continuous physical characteristics of the wall are characterized by pixelblock,which is introduced into the signal model.Then,on the basis of least absolute shrinkage and selection operator (LASSO) model,a robust optimization objective function is constructed under majorization-minimization (MM) framework.Finally,the corresponding iterative process is deduced by using time shift characteristic of the echo signal of wall and the convolution in time domain.The results show that this method guarantees the contour characteristics of the wall and also suppresses the clutter of the wall image,and furthermore,significantly saving the imaging time.关键词
墙体成像/优化最小化框架/块特性矩阵/LASSO模型/像素块Key words
wall imaging/majorization-minimization framework/block characteristic matrix/LASSO model/pixelblock分类
信息技术与安全科学引用本文复制引用
冯飞,晋良念,刘琦..基于优化最小化框架的墙体成像算法[J].雷达科学与技术,2018,16(1):37-42,6.基金项目
国家自然科学基金(No.61461012) （No.61461012）
广西无线宽带通信与信号处理重点实验室2016主任基金项目(No.GXKL06160106) （No.GXKL06160106）
