A Fully Automatic Autofocusing Algorithm for Post-processing ISAR Imaging based on Image Entropy Minimization
AbstractAutofocus is a technique for improving inverse synthetic aperture radar (ISAR) imaging. In this paper, a novel autofocusing method is developed for high-resolution stepped-frequency ISAR. Non-uniform rotational motion is compensated through the proposed post-processing methodology. In this way, the computational cost of polar reformatting process can be circumvented. The proposed CPI-split autofocusing process results in well-focused ISAR images for high angular acceleration periods. Finally, ISAR image entropy dependencies are thoroughly examined through various simulation results, leading to an acceptable range of entropy values for the autofocusing process. Ill. 7, bibl. 9, tabl. 3 (in English; abstracts in English and Lithuanian).
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