基于块稀疏信号重构的高分辨率ISAR成像算法

冯俊杰<sup>1,2</sup>,张弓<sup>1</sup>

doi:10.13718/j.cnki.xsxb.2018.10.014

西南师范大学学报(自然科学版)

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基于块稀疏信号重构的高分辨率ISAR成像算法

冯俊杰1,2,张弓1. 基于块稀疏信号重构的高分辨率ISAR成像算法[J]. 西南师范大学学报(自然科学版), 2018, 43(10): 74-79. doi: 10.13718/j.cnki.xsxb.2018.10.014

引用本文:

冯俊杰^1,2,张弓¹. 基于块稀疏信号重构的高分辨率ISAR成像算法[J]. 西南师范大学学报(自然科学版), 2018, 43(10): 74-79. doi: 10.13718/j.cnki.xsxb.2018.10.014

FENG Jun-jie1,2, ZHANG Gong1. High Resolution ISAR Imaging Algorithm Based on Block Sparse Signal Recovery[J]. Journal of Southwest China Normal University(Natural Science Edition), 2018, 43(10): 74-79. doi: 10.13718/j.cnki.xsxb.2018.10.014

Citation:

FENG Jun-jie^1,2, ZHANG Gong¹. High Resolution ISAR Imaging Algorithm Based on Block Sparse Signal Recovery[J]. Journal of Southwest China Normal University(Natural Science Edition), 2018, 43(10): 74-79. doi: 10.13718/j.cnki.xsxb.2018.10.014

基于块稀疏信号重构的高分辨率ISAR成像算法

冯俊杰^1,2,张弓¹

1. 南京航空航天大学电子信息工程学院, 南京 211106;
2. 六盘水师范学院电气工程学院, 贵州六盘水 553004

High Resolution ISAR Imaging Algorithm Based on Block Sparse Signal Recovery

FENG Jun-jie^1,2, ZHANG Gong¹

1. College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
2. School of Electrical engineering, Liupanshui Normal University, Liupanshui, Guizhou, 553004, China

摘要: 为实现快速高分辨率逆合成孔径雷达（Inverse synthetic aperture radar，ISAR）成像，充分利用目标的内在块稀疏结构信息，提出一种块平滑l0范数稀疏重构ISAR成像算法.首先，将ISAR稀疏成像转化为块l0范数的优化问题，采用一阶负指数函数趋近块l0范数.其次，采用单循环步骤代替平滑l0范数算法中的双循环结构，减小控制参数的间隔，实现对块稀疏信号的优化重构.该算法能够在块稀疏度未知时利用ISAR目标固有的内在结构特征进行高分辨率成像.仿真实验结果证实该算法的成像质量高且快于其它算法.
- 逆合成孔径雷达 /
- 块稀疏信号 /
- 平滑函数 /
- 成像
Abstract: To achieve fast high resolution inverse synthetic aperture radar (ISAR) imaging, a block sparse signal recovery ISAR imaging algorithm based on smoothed l0 norm is proposed by utilizing the block structure of the scatters. Firstly, the ISAR sparse imaging problem is mathematically converted into block l0 norm sparse optimization problem, one negative exponential function sequence approaches the block l0 norm. Then, a single loop structure is proposed to instead of the double loop layers in the smoothed l0 algorithm to solve the sparse signal recovery problem, the interval of controlling parameter decreases, the block sparse signal can be recovery precisely. The proposed method can be applied to ISAR imaging by exploiting the underlying block sparse structures, which doesn't need the information of the number of the blocks. Simulation and real data experiments verify that the quality of the ISAR image using the algorithm of this paper is higher and the speed is faster than other algorithms.
- Inverse Synthetic Aperture Radar (ISAR) /
- block sparse signal /
- smoothed function /
- imaging .

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基于块稀疏信号重构的高分辨率ISAR成像算法

冯俊杰^1,2,张弓¹

1. 南京航空航天大学电子信息工程学院, 南京 211106;
2. 六盘水师范学院电气工程学院, 贵州六盘水 553004

收稿日期: 2017-08-28

关键词:

摘要: 为实现快速高分辨率逆合成孔径雷达（Inverse synthetic aperture radar，ISAR）成像，充分利用目标的内在块稀疏结构信息，提出一种块平滑l0范数稀疏重构ISAR成像算法.首先，将ISAR稀疏成像转化为块l0范数的优化问题，采用一阶负指数函数趋近块l0范数.其次，采用单循环步骤代替平滑l0范数算法中的双循环结构，减小控制参数的间隔，实现对块稀疏信号的优化重构.该算法能够在块稀疏度未知时利用ISAR目标固有的内在结构特征进行高分辨率成像.仿真实验结果证实该算法的成像质量高且快于其它算法.

English Abstract

High Resolution ISAR Imaging Algorithm Based on Block Sparse Signal Recovery

1. 南京航空航天大学电子信息工程学院, 南京 211106;
2. 六盘水师范学院电气工程学院, 贵州六盘水 553004

Received Date: 2017-08-28

Keywords:

Abstract: To achieve fast high resolution inverse synthetic aperture radar (ISAR) imaging, a block sparse signal recovery ISAR imaging algorithm based on smoothed l0 norm is proposed by utilizing the block structure of the scatters. Firstly, the ISAR sparse imaging problem is mathematically converted into block l0 norm sparse optimization problem, one negative exponential function sequence approaches the block l0 norm. Then, a single loop structure is proposed to instead of the double loop layers in the smoothed l0 algorithm to solve the sparse signal recovery problem, the interval of controlling parameter decreases, the block sparse signal can be recovery precisely. The proposed method can be applied to ISAR imaging by exploiting the underlying block sparse structures, which doesn't need the information of the number of the blocks. Simulation and real data experiments verify that the quality of the ISAR image using the algorithm of this paper is higher and the speed is faster than other algorithms.