We consider the data-driven motion compensation problem in inverse synthetic aperture radar (ISAR) imaging. We present optimization-based ISAR techniques and propose improvements to the range alignment, time-window selection, autofocus, time-frequency-based image reconstruction, and cross-range scaling procedures. In experiments, the improvements reduced the computational burden and increased the image contrast by 50% at best and 28% on average in several test cases, including changing translational and rotational motion.
Data-Driven Motion Compensation Techniques for Noncooperative ISAR Imaging
IEEE Transactions on Aerospace and Electronic Systems ; 54 , 1 ; 295-314
2018-02-01
938611 byte
Article (Journal)
Electronic Resource
English
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