Results on Super-Resolution and Target Identification Techniques From the SPERI Project
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 Ap...
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| Veröffentlicht in: | IEEE aerospace and electronic systems magazine 2021-03, Vol.36 (3), p.24-35 |
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| container_title | IEEE aerospace and electronic systems magazine |
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| creator | Bruggenwirth, Stefan Wagner, Simon Bieker, Tanja Battisti, Nicola Rispoli, Vincenzo Greco, Mario Pinelli, Gianpaolo Cataldo, Davide Martorella, Marco |
| description | 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. |
| doi_str_mv | 10.1109/MAES.2020.3039849 |
| format | Magazinearticle |
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| source | IEEE Electronic Library (IEL) |
| subjects | Airborne radar Airborne sensing Algorithms Apodization Bandwidth Compressed sensing Inverse synthetic aperture radar Radar Radar imaging Radar signal processing Radar targets Research and development Signal processing Signal processing algorithms Superresolution Target recognition |
| title | Results on Super-Resolution and Target Identification Techniques From the SPERI Project |
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