A Novel Three-Dimension Imaging Algorithm Based on Trajectory Association of ISAR Image Sequence

Due to scatterer occlusion and missing during the observation time, the acquisition of the complete scatterer trajectory matrix is a hard task, which is the most important process in 3-D inverse synthetic aperture radar (ISAR) imaging of space targets based on 2-D ISAR image sequence. To cope with this problem, a novel fast scatterer trajectory association algorithm based on the cluster-based nearest neighbor standard filter (CNNSF) combined with the general Hough transform (GHT) is proposed. First, a modified dynamic equation for Kalman filter (KF) based on the scatterer projected trajectory model is derived. Then the state vector and covariance for the new dynamic equation are initialized by utilizing the GHT. Finally, the complete scatterer trajectory matrix is achieved efficiently by utilizing the proposed trajectory association algorithm based on the CNNSF algorithm. Simulation results demonstrate the correctness of the dynamic equation and the effectiveness of the proposed algorithm.