Results on Super-Resolution and Target Identification Techniques From the SPERI Project

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
Hauptverfasser: Bruggenwirth, Stefan, Wagner, Simon, Bieker, Tanja, Battisti, Nicola, Rispoli, Vincenzo, Greco, Mario, Pinelli, Gianpaolo, Cataldo, Davide, Martorella, Marco
Format: Magazinearticle
Sprache:eng
Schlagworte:
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
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Beschreibung
Zusammenfassung: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.
ISSN:0885-8985
1557-959X
DOI:10.1109/MAES.2020.3039849