Range alignment plays an important role in the inverse synthetic aperture radar (ISAR) imaging. The performance of the traditional range alignment algorithms decreases when the migration through resolution cells (MTRC) is much severe. In this paper, a measure of MTRC is defined, and the effect of MTRC on range alignment is analyzed. Taking MTRC into account, a robust sub-integer range alignment algorithm is proposed. Firstly, each range profile is interpolated to remove the precision limitation of integer range resolution cell. Subsequently, the matrix formed by all the range profiles is partitioned into several matrix blocks on the slow-time domain. For each matrix block, the range profiles are aligned by minimizing the entropy of the average range profile (ARP). Finally, the matrix blocks are coarsely aligned using the maximum correlation method, followed by a fine alignment based on the minimization of the ISAR image entropy. The effectiveness of the proposed algorithm is validated by simulations and real-world data. Results demonstrate that the proposed method is robust against MTRC and can reduce the alignment error. The resultant ISAR image is much better focused.
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