Exact Observation Based Phase Preservation Bistatic SAR Sparse Imaging: Initial Result

Due to the capability of acquiring non-backscattering information, bistatic synthetic aperture radar (BiSAR) extends the application scope of synthetic aperture radar (SAR). Sparse SAR imaging has demonstrated remarkable potential in enhancing the recovered image quality. However, traditional regularization reconstruction algorithms for sparse SAR imaging fail to maintain the background distribution of the image and completely disrupt its phase. To address above problem, this paper proposes a phase-preserving BiSAR sparse imaging method. The proposed method firstly constructs an exact observation matrix to achieve deconvolution of the BiSAR echo. Then, it employs an improved iterative soft thresholding (IST) algorithm to solve the L
1
norm regularization problem for scene recovery. The results of the experiment indicate that the proposed method outperforms traditional regularization reconstruction algorithms by achieving both sparse imaging of the observed scene and maintaining phase information through a non-sparse estimation.