Microwave Computational Imaging Technology Based on Deep Unfolding Network

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. © 2024 Chinese Institute of Electronics. All rights reserved.