SAP-ISTA-Net: Synthetic Aperture Processing Assisted ISTA Network for Multichannel Radar Forward-Looking Superresolution Imaging

作者：Wenchao Li, Rui Chen, Ming‐Ming Zhou, Yin Zhang, Ziwen Wang, Wei Pu, Junjie Wu, Jianyu Yang · 发表于：IEEE Sensors Journal · 年份：2025 · DOI：10.1109/jsen.2025.3551167 · 被引用次数：6 · 研究领域：Photoacoustic and Ultrasonic Imaging、Advanced SAR Imaging Techniques、Ultrasound Imaging and Elastography

With azimuth multichannel receiving echoes, multichannel radar can realize forward-looking imaging, but its azimuth resolution is greatly restricted by the platform size. Although many superresolution algorithms have been developed in recent years, they always face problems such as difficulty in parameter tuning, high computational complexity, and noise sensitivity. In this article, a synthetic aperture processing assisted iterative shrinkage thresholding algorithm (ISTA) network, that is, the synthetic aperture processing assisted ISTA network (SAP-ISTA-Net), is proposed to achieve multichannel radar forward-looking superresolution imaging. In the network, the reconstruction process with ISTA is mapped into a deep unfolding network, and the real aperture superresolution imaging with ISTA-Net is achieved by processing the instantaneous data of multiple channels first. Then, the superresolution result is enhanced by the synthetic aperture processing of one-channel data with different time instants. At last, simulated and measured data experiments are presented to verify the effectiveness of the proposed method.