Interferometric Phase Restoration for Non-Common Band Imaging Via a Physics-Aware Spectrum Fusion Network

The Synthetic Aperture Radar (SAR) system has undergone significant advancements, transitioning into a multi-functional platform with various modes. This study introduces a novel imaging mode that enables the simultaneous acquisition of height and intensity features, addressing the diverse requirements of different regions. Referred to as non-common band imaging, this mode optimizes bandwidth allocation within the limited illumination time, enhancing efficiency and flexibility. However, the interferometric phase retrieval problem arises in this mode. To address this challenge, we establish a forward model for the master-slave images and propose an optimization-solving model that incorporates wavelet sparsity regularization to mitigate noise interference. Furthermore, we introduce a physics-aware spectrum fusion network, combining proximal gradient descent methodology with the innovative deep unfolding technique, to restore the interferometric phase. Extensive experiments conducted on simulated and real measured data validate the effectiveness of the proposed network in terms of efficiency, accuracy, and noise reduction capabilities.