volume | PIER Journals

Abstract

Millimeter wave synthetic aperture interferometric radiometer (SAIR) can achieve high-resolution imaging without a large physical aperture antenna and has strong application advantages in the fields of earth remote sensing, astronomical observation, and meteorological monitoring. In order to adapt to various payload platforms and detection needs, the existing SAIR array structures are diverse, but the existing imaging methods are difficult to effectively deal with various arrays and achieve stable high-precision imaging inversion. Thus, this paper proposes a general multi-channel fusion imaging network to achieve SAIR imaging inversion of any array structure. First, with the help of the sensor matrix deduction subnet, a high-precision imaging sensor matrix is deduced according to the position of each array element of the SAIR system, and then high-precision image reconstruction is achieved with the help of the multi-channel fusion imaging subnet. The simulation results show that the network has good adaptability and can achieve high-precision imaging inversion of different SAIR array structures.

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Dr. Chenggong Zhang

Professor Jianfei Chen

Dr. Jiahao Yu

Dr. Yujie Ruan

Dr. Sheng Zhang

Dr. Shujin Zhu

Dr. Leilei Liu