Autofocusing of ISAR images based on entropy minimization
| Autor: | Liu Guosui, Jinlin Ni, Li Xi |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Synthetic aperture radar
Motion compensation Computer science business.industry Pulse-Doppler radar ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Aerospace Engineering Side looking airborne radar Image processing Continuous-wave radar Inverse synthetic aperture radar Radar engineering details Computer Science::Computer Vision and Pattern Recognition Radar imaging Computer vision Artificial intelligence Electrical and Electronic Engineering business Physics::Atmospheric and Oceanic Physics |
| Zdroj: | IEEE Transactions on Aerospace and Electronic Systems. 35:1240-1252 |
| ISSN: | 0018-9251 |
| DOI: | 10.1109/7.805442 |
| Popis: | A novel autofocusing technique is developed for random translational motion compensation in inverse synthetic aperture radar (ISAR) imaging of objects. This technique is based on an entropy minimization principle and validated via a nonparametric estimation method. Images of a simulation and a real flying aircraft are used for illustration. Images of encouraging quality confirm the feasibility of autofocusing the radar images by just the requirement of minimizing the image entropy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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