TWIST-SBRIM: A Novel Efficient and Robust Approach for Compressive Sensing with Application to SAR Tomography

Tomography synthetic aperture radar (TomoSAR) realizes 3D imaging by using multi-baseline acquisitions in the elevation direction. And the elevation resolution depends on the elevation aperture. However, in practice, due to the limited track number or non-uniform distribution of the spatial baseline, the elevation resolution of the traditional methods, such as Fourier transform, the back-projection algorithm and spectral estimation is lower. Compressive sensing (CS) methods can achieve high elevation resolution, while often can't guarantee computation efficiency. To address these difficulties, a novel efficient and robust CS algorithm named TWIST-SBRIM is proposed and used for TomoSAR 3D imaging. In this paper, we firstly establish a TomoSAR linear measurement model. Then the TWIST-SBRIM algorithm is used to realize the TomoSAR 3D inversion. Both simulated data and measured data of TerraSAR-X system are used. 3D image reconstruction results show that the proposed method outperforms traditional methods regarding efficiency and accuracy under the low signal-to-noise ratio (SNR) condition, which proves the validity and practicality of the proposed method.