Abstract:The advancement of spaceborne inverse synthetic aperture radar (ISAR) imaging for on-orbit target represents a critical technology for space situational awareness (SSA). While conventional two-dimensional (2D) range-Doppler (RD) imaging provides valuable scattering intensity distributions, it inherently is the projection of the target’s three-dimensional (3D) structure, thereby losing critical geometric information essential for predicting orbital maneuvers and enabling non-cooperative target recognition. Current multi-views reconstruction methods based on image sequences face inherent limitations in spaceborne scenarios: the relative orbital motion between the spaceborne platform and target satellite induces limited observation time and unstable imaging projection plane. To address these challenges, a target reconstruction algorithm with variable observation mode is proposed. First, the structural information contained in range migration (RM) trajectories is directly exploited to avoid the error-prone image alignment process. Second, we derive a unified geometric model characterizing the range migration (RM) evolution under both 2D and 3D rotation patterns, and extract discriminative features for rotation pattern classification. Finally, we develop a high-precision RM estimation algorithm based on higher-order Doppler coefficient estimation. For different rotation modes, a truncated nuclear norm (TNN) regularization combined with factorization framework enables the reconstruction of 2D or 3D targets under observation error conditions. Simulation results demonstrate that the proposed target reconstruction algorithm effectively achieves scattering point extraction and RM matrix reconstruction. It further ensures the regularized convergence of the RM matrix, thereby obtaining spatial target reconstruction results under various rotation states. This validates the effectiveness and flexibility of the proposed algorithm.
