DipSAR: Deep Image Prior for Sparse Sampled Near-Field SAR Millimeter-Wave Imaging

We present a deep learning-based approach called DipSAR for reconstructing millimeter-wave synthetic aperture radar (SAR) images from sparse samples. The primary challenge lies in the requirement of a large training dataset for deep learning schemes. To overcome this issue, we employ the deep image prior (DIP) technique, which eliminates the...