Efficient 3D imaging method of MIMO radar for moving target

Wei WANG; Ziying HU; Jia’nan YUE

doi:10.11959/j.issn.1000-436x.2019140

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Efficient 3D imaging method of MIMO radar for moving target

Papers | 更新时间：2024-06-05

- Efficient 3D imaging method of MIMO radar for moving target
- Journal on Communications Vol. 40, Issue 7, Pages: 38-47(2019)
- 作者机构：
  
  哈尔滨工程大学自动化学院，黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61571148);The National Natural Science Foundation of China(61871143);The Fundamental Research Funds for the Central Universities(HEUCFG201823);The Fundamental Research Funds for the Central Universities(3072019CF0402);The Natural Science Foundation of Heilongjiang Province(LH2019F006);The Research and Development Project of Application Technology in Harbin(2017R-AQXJ095)
- DOI：10.11959/j.issn.1000-436x.2019140
  CLC： TN958
- Online First：2019-07，
  
  Published：25 July 2019
- 稿件说明：
移动端阅览
Wei WANG, Ziying HU, Jia’nan YUE. Efficient 3D imaging method of MIMO radar for moving target[J]. Journal on Communications, 2019, 40(7): 38-47.
DOI：

Wei WANG, Ziying HU, Jia’nan YUE. Efficient 3D imaging method of MIMO radar for moving target[J]. Journal on Communications, 2019, 40(7): 38-47. DOI： 10.11959/j.issn.1000-436x.2019140.

摘要

利用压缩感知实现运动目标的稀疏成像时，运动引起的多普勒频移会增加模型维度，改变回波的中心频率，并影响测量矩阵的互相干特性。为了改善MIMO雷达对运动目标的三维成像性能，提出了一种高效的成像方法，在各维分别搜索目标的分布信息，并由该信息作为索引重构新的低维测量矩阵，借此缩小目标区域范围，同时基于测量矩阵的互相干性，应用贝叶斯方法实现多普勒维度投影矩阵的优化，降低多普勒频率采样带来的强相干性，实现高效稀疏成像。仿真结果表明，所提方法可以明显地提升运算效率，具有高效精确的成像性能。

Abstract

When compressive sensing (CS) was used to achieve sparse imaging of moving targets

the Doppler frequency caused by motion will increase the processing dimension

change the center frequency of echo and worsen the mutual coherence property of measurement matrix.In order to improve the three-dimensional (3D) imaging performance of MIMO radar for moving targets

an efficient method was proposed.In each dimension

the distribution information of targets was searched respectively and a new low-dimensional measurement matrix was reconstructed accordingly

so the targets’ area was narrowed down.At the same time

in order to optimize the mutual coherence property of measurement matrix

Bayesian method was used to optimize the velocity-dimensional projection matrix to reduce the strong mutual coherence brought by sampling of Doppler frequency

then the efficient sparse imaging could be achieved.The simulation results show that proposed method can improve the efficiency

accurate imaging performance with efficient.

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Keywords

references

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