电子学报2024，Vol.52Issue(12)：4048-4058,11.DOI:10.12263/DZXB.20230920
基于深度展开网络的微波计算成像技术
Microwave Computational Imaging Technology Based on Deep Unfolding Network
摘要
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 electromag-netic waves,thereby bringing new physical phenomena.Information Metamaterial Aperture-based Microwave Computation-al 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 recon-struct 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 pa-rameters of the system change.Experimental results show that the proposed method has good imaging performance and ro-bustness.关键词
微波计算成像/信息超材料/相位恢复/深度学习/超网络Key words
microwave computational imaging/information metamaterials/phase retrieval/deep learning/hypernetwork分类
信息技术与安全科学引用本文复制引用
史洪印,彭毓晗,温裕广,黎芳,刘慧..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):4048-4058,11.基金项目
国家自然科学基金(No.62071414) （No.62071414）
北京市教育委员会科技计划(No.KZ202210016021) National Natural Science Foundation of China(No.62071414) （No.KZ202210016021）
Research and Devolopment Program of Beijing Municipal Education Commission(No.KZ202210016021) （No.KZ202210016021）
