A novel motion compensation algorithm for spaceborne inverse synthetic aperture radar imaging of air target under low signal-to-noise ratio condition

The spaceborne Inverse Synthetic Aperture Radar (ISAR) has garnered significant attention due to its extensive observation range and robust anti-attack capabilities. Consequently, the ISAR imaging research of air targets based on a spaceborne platform has crucial application value. However, unlike the traditional ground-based radar system, the spaceborne platform moves along its own orbit while observing the air target, and the received signal energy is weakened due to the extended observation distance. Therefore, it is important to optimise the existing ISAR imaging geometry models and motion compensation algorithms. The authors first construct a geometric model of spaceborne ISAR imaging for air targets. Aiming at the problem of low signal-to-noise ratio (SNR), a novel translational motion compensation algorithm based on motion parameter estimation is proposed. The algorithm compensates for both distance migration and Doppler migration caused by the first-order and second-order motion components of relative motion, respectively. Finally, simulation and semi-physical simulation results validate the effectiveness and superiority of the proposed algorithm under different SNR and motion conditions.