Data-driven motion compensation techniques for noncooperative ISAR imaging
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||IEEE Transactions on Aerospace and Electronic Systems|
|Early online date||26 Sep 2017|
|Publication status||Published - Feb 2018|
|Publication type||A1 Journal article-refereed|
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 crossrange scaling procedures. In experiments, the improvements reduced the computational burden and increased the image contrast by 50 percent at best and 28 percent on average in several test cases including changing translational and rotational motion.