Satellite-to-satellite Linear Array SAR 3D Backward Projection Super-Resolution Imaging Algorithm with Compressed Sensing

Aiming at the difficulty of satellite-to-satellite 3D imaging caused by the long revisit time of tomographic synthetic aperture radar and the complex relative motion between satellites, this paper proposes a fast satellite-to-satellite 3D super-resolution imaging algorithm based on the linear array synthetic aperture radar (LA-SAR) system. The algorithm combines backward projection (BP) with compressed sensing (CS), overcomes the difficulty of insufficient resolution of LA-SAR, and can perform 3D super-resolution imaging of any near-neighbor orbit satellite with only one synthetic aperture time, without being limited by the satellite motion trajectory. In addition, the proposed method can adaptively reduce the solution space of the target imaging dictionary to reduce the dimension of the sensing matrix based on the two-dimensional SAR image information of the target, thus realizing the fast convergence of the algorithm. Simulation analysis and experimental results show that this method can not only obtain the 3D super-resolution image of the target, but also has fast imaging speed.