1. Results on Super-Resolution and Target Identification Techniques From the SPERI Project
- Author
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Mario Greco, Tanja Bieker, Simon Wagner, Marco Martorella, Nicola Battisti, Davide Cataldo, Vincenzo Rispoli, G. Pinelli, Stefan Bruggenwirth, and Publica
- Subjects
Computer science ,Aerospace Engineering ,02 engineering and technology ,Radar, Automatic Target Recognition, Target Identification, Super-Resolution, SAR, ISAR, radar imaging ,law.invention ,ISAR ,0203 mechanical engineering ,Apodization ,law ,Radar imaging ,Computer vision ,Electrical and Electronic Engineering ,Radar ,020301 aerospace & aeronautics ,Signal processing ,Super-Resolution ,business.industry ,Bandwidth (signal processing) ,radar imaging ,Inverse synthetic aperture radar ,Identification (information) ,Compressed sensing ,Space and Planetary Science ,Artificial intelligence ,Automatic Target Recognition ,Target Identification ,business ,SAR - Abstract
We give an overview of the EDA CAT B R&D project ""Signal Processing for Enhanced Radar Imaging"" (SPERI). In this project, the benefits of applying two super-resolution methods Super Spatially Variant Apodization (SSVA) and Compressed Sensing (CS) to two-dimensional Inverse Synthetic Aperture Radar (ISAR) images of airborne radar targets were investigated with respect to the improvements in automatic target identification rates. The algorithms have been tested over a database of more than 1200 real radar images.
- Published
- 2021