Scatterer Trajectory Association Based on Motion Model for ISAR Image Sequence and Analysis of Influence Factors

For the three-dimensional inverse synthetic aperture radar (3-D ISAR) imaging of space targets from two-dimensional (2-D) ISAR image sequence, obtaining a complete trajectory matrix via scatterer trajectory association is critical. Motion model-based trajectory association involves establishing the motion model of scatterers’ projected trajectories on the ISAR image projection plane and achieving association. In this paper, a motion model is established and a scatterer trajectory association algorithm based on multiple hypothesis tracking (MHT) combined with the Rauch-Tung-Striebel algorithm is proposed. First, the motion model is provided, and on the basis of this model, the dynamic equation for Kalman filtering is derived. To extract observations for scatterer trajectory association from the ISAR image sequence, an ISAR cross-range scaling algorithm and an observation extraction algorithm are introduced. In addition, a detailed analysis about the influences of various factors on the scatterer trajectory association is conducted, such as cross-range scaling error, observation extraction error, anisotropy of the scattering coefficient and physical occlusion. Then, the proposed scatterer trajectory association algorithm is implemented to obtain the complete trajectory matrix. The proposed algorithm can improve the estimation accuracy of the state vectors by fully utilizing all the observations to smooth the estimated state vectors. Finally, simulation results validate the effectiveness and robustness of the proposed algorithm in the presence of these factors.