Long-Time Coherent Integration and Detection for Asteroid Targets in a Space-based Radar System Based on Particle Swarm Optimization

The space-based surveillance radar system has a higher field of view and can overcome interference from Earth's atmosphere and terrain occlusion, which has been widely applied in high-threat near-Earth asteroid (NEA) warning and defense applications. Due to the limited power aperture product of the space-based system and the far distance between the radar and asteroid targets, the target signal is extremely weak. Prolonging the coherent accumulation time can effectively improve the radar detection capability of small asteroid targets, but the complex effects of range migration (RM) and Doppler frequency migration (DFM) will degrade the target coherent accumulation performance. To effectively solve this problem, an improved Keystone transform (KT) matched filtering banks method based on particle swarm optimization algorithm is proposed. Compared with traditional methods, the proposed method can not only ensure that the asteroid target detection performance is close to the theoretical optimum, but also reduce the system computation complexity. Simulation results verify the effectiveness of the proposed algorithm.