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弹箭与制导学报 >

2019 , Vol. 39 >Issue 3: 115 - 118

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2019.03.026

模式耦合快速求逆稀疏贝叶斯 MIMO雷达成像

  • 胡仁荣 ,
  • 童宁宁 ,
  • 何兴宇 ,
  • 陈桥
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  • 空军工程大学防空反导学院,西安 710051

胡仁荣(1993-),男,浙江台州人,硕士研究生,研究方向:MIMO雷达成像。

收稿日期: 2018-06-14

  网络出版日期: 2025-05-20

基金资助

国家自然科学基金(6157010318)

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MIMO Radar Imaging Based on Pattern – coupled Fast Inverse – freeSparse Bayesian Learning

  • HU Renrong ,
  • TONG Ningning ,
  • HE Xingyu ,
  • CHEN Qiao
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  • Air Defense and Anti-missile Institute, Air Force Engineering University, Xi'an 710051, China

Received date: 2018-06-14

  Online published: 2025-05-20

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摘要

MIMO雷达成像目标通常具有块稀疏特性,模式耦合稀疏贝叶斯算法能够较好的恢复块稀疏信号,但其主要的缺点是在每次迭代过程中都涉及复杂矩阵求逆。引入快速求逆稀疏贝叶斯算法,建立模式耦合快速求逆稀疏贝叶斯模型,将复杂矩阵求逆转化为对角矩阵求逆,实现MIMO雷达目标快速精确重构。通过仿真对比分析,所提算法较传统贝叶斯算法能大大减少雷达成像时间,且实现目标块区域信息高效恢复。

关键词： MIMO雷达成像; 模式耦合; 块稀疏; 快速求逆

本文引用格式

胡仁荣 , 童宁宁 , 何兴宇 , 陈桥 . 模式耦合快速求逆稀疏贝叶斯 MIMO雷达成像[J]. 弹箭与制导学报, 2019 , 39(3) : 115 -118 . DOI: 10.15892/j.cnki.djzdxb.2019.03.026

Abstract

MIMO radar imaging target usually has a block sparse characteristic, Pattern-coupled sparse Bayesian algorithm can better restore block sparse signals, but its main drawback is that in each iteration involves the complex matrix inverse. Combining the pattern-coupled sparse Bayesian algorithm with the fast inverse sparse Bayesian algorithm, a pattern-coupled fast inverse sparse Bayesian algorithm is set up, which will reverse complex matrix inverse into diagonal dimensional matrix inversion, and realize the MIMO radar target quickly and accurately refactoring. Through the simulation analysis, compared with traditional algorithm, the proposed algorithm can greatly reduce the imaging time, and the realize the efficient recovery of the target.

Key words： MIMO radar imaging; pattern coupled; block sparse; fast inverse

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参考文献

[1]
WANG L, ZHAO LF, BIGA, et al. Enhanced ISAR imaging by exploiting the continuity of the target scene[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014. 52 9: 5736- 5750.
[2]
ELDAR Y C, KUPPINGER P, BOLCSKEI H. Block-sparse signals: uncertainty relations and efficient recovery[J]. IEEE Transactions on Signal Processing, 2010. 58 6: 3042- 3054.
[3]
ELDAR Y C, MISHALI M. Robust recovery of signals from a structured union of subspaces[J]. IEEE Transactions on Information Theory, 2009. 55 11: 5302- 5316.
[4]
FANG J, SHEN Y N, LI H B, et al. Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals[J]. IEEE Transactions on Signal Processing, 2015. 63 2: 360- 372.
[5]
DUAN Huiping, YANG Linxiao, FANG Jun, et al. Fast Inverse-Free sparse Bayesian learning via relaxed evidence lower bound maximization[J]. IEEE Signal Processing Letters, 2017. 24 6: 774- 778.
[6]
周剑雄. 光学区雷达目标三维散射中心重构理论与技术[D]. 长沙: 国防科学技术大学, 2006.
[7]
MA CZ, YEO TS, TAN CS, et al. Three-dimensional imaging of targets using colocated MIMO radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011. 49 8: 3009 3021.
[8]
YANG JC, SU W M, GU H. 3D imaging using narrowband bistatic MIMO radar[J]. Electronics Letters, 2014. 50 15: 1090 1092.
[9]
TIPPING ME. Sparse Bayesian learning and relevance vector machine[J]. Journal of Machine Learning Research, 2001 1: 211- 244.
[10]
TZIKAS D G, LIKAS A C, GALATSANOS N P. The variational approximation for Bayesian inference[J]. IEEE Signal Processing Magazine, 2008. 25 6: 131– 146.
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