A Diffusion Model-Based Unsupervised Method for Active Jamming Suppression of Synthetic Aperture Radar Images

The active jamming suppression of Synthetic Aperture Radar (SAR) images remains a severe challenge. The jamming SAR images simulation dataset is firstly built by open SSDD dataset and random shift-frequency jamming type; The formula of existing diffusion model is then modified using the low-rank based block space filter (BSF) theory; Lastly, jamming SAR images are as the inputs to effectively train our proposed model to generate the jamming suppressed images. Experimental results qualitatively and quantitatively demonstrate the effectiveness of the proposed method.