FDA-3D-SAR imaging based on Bayesian compressed sensing

In view of the large amount of data to be processed by the Frequency Diversity Array three-dimensional Synthetic Aperture Radar (FDA-3D-SAR) system and the higher side lobes of traditional imaging algorithms, this paper proposes a FDA-3D-SAR imaging method based on Bayesian compressed sensing (BCS) reconstruction. This method combines the characteristics of the FDA to make three-dimensional sparse observation of the target. In the imaging part, the BCS algorithm is used to reconstruct the scattering coefficient of the space target. The experimental results show that the proposed method effectively suppresses the side lobes of the radar image and improves the imaging quality.