基于改进OMP算法的稀疏目标微波关联成像方法

doi:10.12305/j.issn.1001-506X.2021.07.04

系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (7): 1756-1765.doi: 10.12305/j.issn.1001-506X.2021.07.04

• 雷达稀疏信号处理技术专栏 • 上一篇下一篇

基于改进OMP算法的稀疏目标微波关联成像方法

张瑞¹, 全英汇^2,*, 朱圣棋¹, 李亚超¹, 邢孟道¹

1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西西安 710071
2. 西安电子科技大学电子工程学院, 陕西西安 710071

收稿日期:2020-12-29 出版日期:2021-06-30 发布日期:2021-07-08
通讯作者: 全英汇
作者简介:张瑞(1995—), 女, 博士研究生, 主要研究方向为空间谱估计、阵列雷达信号处理和雷达抗干扰技术|全英汇(1981—), 男, 教授, 博士, 主要研究方向为雷达电子对抗、雷达实时信号处理和微波遥感|朱圣棋(1984—), 男, 教授, 博士, 主要研究方向为高速平台雷达多目标检测|李亚超(1980—), 男, 教授, 博士, 主要研究方向为SAR/ISAR成像和实时信号处理|邢孟道(1974—), 男, 教授, 博士, 主要研究方向为SAR/ISAR成像和动目标检测等
基金资助:
国家自然科学基金(61772397);国家重点研发计划(2016YFE0200400);陕西省科技创新团队(2019TD-002)

Microwave correlation imaging method based on improved OMP algorithm for sparse targets

Rui ZHANG¹, Yinghui QUAN^2,*, Shengqi ZHU¹, Yachao LI¹, Mengdao XING¹

1. National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China
2. School of Electronic Engineering, Xidian University, Xi'an 710071, China

Received:2020-12-29 Online:2021-06-30 Published:2021-07-08
Contact: Yinghui QUAN

摘要/Abstract

摘要：

利用稀疏重构类方法进行雷达微波关联成像时, 传统的正交匹配追踪(orthogonal matching pursuit, OMP)算法在每一次迭代过程中均需要求解目标函数的最小二乘解, 导致成像算法计算复杂度随矩阵规模和迭代次数增加而急剧攀升。针对此问题, 结合频率捷变思想, 提出了一种改进OMP算法的稀疏目标微波关联成像方法。首先, 阐明了微波关联成像机理, 并构建了微波关联成像信号模型; 然后, 利用共轭梯度法对OMP算法中的最小二乘求解步骤进行了改进, 并分析了改进后算法的计算量; 最后, 通过与最小二乘成像方法、匹配滤波成像方法和基于传统OMP稀疏重构的成像方法进行计算机对比仿真实验, 证明了本文算法的正确性与优越性。

关键词: 频率捷变, 前视成像, 空时二维随机辐射场, 稀疏重构, 最小二乘, 共轭梯度, 微波关联

Abstract:

When sparse reconstruction method is used for radar microwave correlation imaging, the traditional orthogonal matching pursuit (OMP) algorithm needs to solve the least square solution of the objective function in each iteration, which leads to a sharp increase in the computational complexity of the imaging algorithm with the increase of the matrix size and the number of iterations. In order to solve this problem, an improved OMP microwave correlation imaging method for sparse targets combined with frequency agility. Firstly, the mechanism of microwave correlation imaging is clarified, and the signal model of microwave correlation imaging is constructed. Then, the least square solution step of OMP algorithm is improved by using conjugate gradient method, and the calculation amount of the improved algorithm is analyzed. Finally, the correctness and superiority of the proposed algorithm is verified by comparative simulation experiments with least square imaging method, matched filtering imaging method and imaging method based on traditional OMP coefficent reconstruction.

Key words: frequency agility, forward looking imaging, random radiation field, sparse reconstruction, least square, conjugate gradient, microwave correlation

中图分类号:

TN95

张瑞, 全英汇, 朱圣棋, 李亚超, 邢孟道. 基于改进OMP算法的稀疏目标微波关联成像方法[J]. 系统工程与电子技术, 2021, 43(7): 1756-1765.

Rui ZHANG, Yinghui QUAN, Shengqi ZHU, Yachao LI, Mengdao XING. Microwave correlation imaging method based on improved OMP algorithm for sparse targets[J]. Systems Engineering and Electronics, 2021, 43(7): 1756-1765.

图/表 12

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参数	数值
脉冲宽度/μs	30
脉冲重复频率/kHz	25
信号带宽/MHz	24
脉冲数/个	32
阵元数/个	16
频率步进量/MHz	9.15
距离向采样点数	4 320
网格数	61×61
网格划分范围/m	X方向: 10~70 Y方向: 10~70
网格大小/m	1×1

调试目标	算法
调试目标	匹配滤波法	最小二乘法	传统OMP算法	改进OMP算法
3个点目标	0.11	7.91	2.10	0.12
飞机目标	0.12	8.06	2.14	0.15

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基于改进OMP算法的稀疏目标微波关联成像方法

Microwave correlation imaging method based on improved OMP algorithm for sparse targets

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