Results on super-resolution and target identification techniques from the SPERI project

Stefan Brüggenwirth; Simon Wagner; Tanja Bieker; Nicola Battisti; Vincenzo Rispoli; Mario Greco; Gianpaolo Pinelli; Davide Cataldo; Marco Martorella

doi:10.1109/MAES.2020.3039849

Results on super-resolution and target identification techniques from the SPERI project

Stefan Brüggenwirth, Simon Wagner, Tanja Bieker, Nicola Battisti, Vincenzo Rispoli, Mario Greco, Gianpaolo Pinelli, Davide Cataldo, Marco Martorella

Engineering

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	24-35
Number of pages	12
Journal	IEEE Aerospace and Electronic Systems Magazine
Volume	36
Issue number	3
Early online date	19 Nov 2020
DOIs	https://doi.org/10.1109/MAES.2020.3039849
Publication status	Published - 1 Mar 2021

Bibliographical note

Publisher Copyright:
© 1986-2012 IEEE.

Keywords

Superresolution
Signal processing algorithms
Bandwidth
Radar imaging
Radar signal processing
Compressed sensing
Research and development
Inverse synthetic aperature radar
Target recognition

ASJC Scopus subject areas

Aerospace Engineering
Space and Planetary Science
Electrical and Electronic Engineering

Access to Document

10.1109/MAES.2020.3039849

Cite this

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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.",

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AU - Greco, Mario

AU - Pinelli, Gianpaolo

AU - Cataldo, Davide

AU - Martorella, Marco

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KW - Compressed sensing

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Results on super-resolution and target identification techniques from the SPERI project

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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