Microwave Computational Imaging Technology Based on Deep Unfolding Network

SHI Hong-yin; PENG Yu-han; WEN Yu-guang; LI Fang; LIU Hui

doi:10.12263/DZXB.20230920

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Microwave Computational Imaging Technology Based on Deep Unfolding Network

PAPERS | 更新时间：2025-12-11

- Microwave Computational Imaging Technology Based on Deep Unfolding Network
- ACTA ELECTRONICA SINICA Vol. 52, Issue 12, Pages: 4048-4058(2024)
- 作者机构：
  
  1.北京建筑大学电气与信息工程学院，北京 100044
  2.建筑大数据智能处理方法研究北京市重点实验室，北京 100044
  3.航天新气象科技有限公司，北京 100048
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62071414);Research and Devolopment Program of Beijing Municipal Education Commission(KZ202210016021)
- DOI：10.12263/DZXB.20230920
  CLC： TN958;
- Received：28 September 2023，
  
  Revised：2024-01-10，
  
  Published：25 December 2024
- 稿件说明：
移动端阅览
史洪印, 彭毓晗, 温裕广, 等. 基于深度展开网络的微波计算成像技术[J]. 电子学报, 2024, 52(12): 4048-4058.

SHI Hong-yin, PENG Yu-han, WEN Yu-guang, et al. Microwave Computational Imaging Technology Based on Deep Unfolding Network[J]. Acta Electronica Sinica, 2024, 52(12): 4048-4058.
史洪印, 彭毓晗, 温裕广, 等. 基于深度展开网络的微波计算成像技术[J]. 电子学报, 2024, 52(12): 4048-4058. DOI：10.12263/DZXB.20230920

SHI Hong-yin, PENG Yu-han, WEN Yu-guang, et al. Microwave Computational Imaging Technology Based on Deep Unfolding Network[J]. Acta Electronica Sinica, 2024, 52(12): 4048-4058. DOI：10.12263/DZXB.20230920

摘要

信息超材料是一种人工结构阵列，其能够通过设计单元参数的排列方式定制等效材料和媒质属性，实现对电磁场和电磁波的灵活调控，带来全新的物理现象.基于信息超材料孔径的微波计算成像（Microwave Computational Imaging based Information Metamaterial Aperture， IMA-MCI）技术可以不依靠于雷达平台与目标之间的相对运动，在波束内实现目标的高分辨率成像.在微波成像过程，由于信息超材料天线的制作工艺限制，可能会导致相位误差的产生，IMA-MCI在有相位误差的情况下，对目标场景的重构能力不足.针对该问题，本文构建了基于反射式信息超材料天线的微波计算成像模型，提出一种结合深度展开网络和相位恢复算法的成像技术.该算法在相位恢复算法的基础上引入了动态超网络为原有网络生成阻尼因子，能够根据输入场景不同进行调整，在线生成阻尼因子，在系统的参数发生变化时仍然具有较好的性能.实验结果显示，该方法具有较好的成像性能和鲁棒性.

Abstract

Information metamaterial is an artificial structure that can customize its equivalent material and media properties by designing unit parameters and arrangement

and realize free control of electromagnetic fields and electromagnetic waves

thereby bringing new physical phenomena. Information Metamaterial Aperture-based Microwave Computational Imaging (IMA-MCI) technology can achieve high-resolution imaging of targets within the beam without relying on the relative motion between the radar platform and the target. In microwave imaging

due to the limitations of the fabrication process of information metamaterial antennas

phase errors may be caused

and it is still challenging for IMA-MCI to reconstruct the target scene under the condition of phase error. To solve this problem

a microwave computational imaging model based on reflective information metamaterial antenna is constructed

and an imaging technology based on the combination of deep unfolding network and phase retrieval algorithm is proposed. Based on the phase retrieval algorithm

the algorithm introduces a dynamic super network to generate damping factors for the original network

and introduces a recurrent neural network

which can generate damping factors online according to the model

and still has good performance when the parameters of the system change. Experimental results show that the proposed method has good imaging performance and robustness.

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references

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