  Synthetic aperture radar is a high-resolution two-dimensional imaging radar,
however, during the imaging process, SAR is susceptible to intentional and
unintentional interference, with radio frequency interference (RFI) being the
most common type, leading to a severe degradation in image quality. Although
inpainting networks have achieved excellent results, their generalization is
unclear, and whether they still work effectively in cross-sensor experiments
needs further verification. Through time-frequency analysis of interference
signals, we find that interference holds domain invariant features between
different sensors. Therefore, this paper reconstructs the loss function and
extracts the domain invariant features to improve the generalization.
Ultimately, this paper proposes a SAR RFI suppression method based on domain
invariant features, and embeds the RFI suppression into SAR imaging process.
Compared to traditional notch filtering methods, the proposed approach not only
removes interference but also effectively preserves strong scattering targets.
Compared to PISNet, our method can extract domain invariant features and holds
better generalization ability, and even in the cross-sensor experiment, our
method can still achieve excellent results.
