XLIM UMR 7252, Université de Limoges/CNRS, 87060 Limoges, France .
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA.
Sensors (Basel). 2018 May 12;18(5):1536. doi: 10.3390/s18051536.
Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical layer. This paper presents a new reconstruction technique leveraging the sparsity of the signals in the time-domain and decomposition of the sensing matrix.
最近在微波和毫米波领域提出了许多计算成像系统的原型，通过使用可以在物理层复用编码信号的辐射腔和超表面，可以简化相关的有源架构。本文提出了一种新的重建技术，利用时域信号的稀疏性和传感矩阵的分解。
