The side-looking imaging geometry of synthetic aperture radar (SAR) causes inevitable layover in SAR images. Separating the contributions from different scatterers has been the fundamental for many applications. It is typically solved by explicit inversion of the SAR imaging model to retrieve the scattering profile along the mixed dimension (elevation), which is otherwise known as SAR tomography. This paper proposed a robust blind scatterer separation method to demix the layovered scatterers, avoiding the computationally expensive tomographic inversion. We demonstrate that the state-of-the-art principle component decomposition-based methods are heavily influenced by the nonergodicity of the selected samples, especially in urban area, such as point scatterers appearing often on facades. The proposed method is shown to be more robust than the state-of-the-art. Real data example shows that the proposed method outperforms the state-of-the-art by a factor of three in terms of the accuracy of the retrieved phase.     «

The side-looking imaging geometry of synthetic aperture radar (SAR) causes inevitable layover in SAR images. Separating the contributions from different scatterers has been the fundamental for many applications. It is typically solved by explicit inversion of the SAR imaging model to retrieve the scattering profile along the mixed dimension (elevation), which is otherwise known as SAR tomography. This paper proposed a robust blind scatterer separation method to demix the layovered scatterers, av...     »