Signal Processing for Enhanced ISAR Imaging

This Project is the follow on of the ERIT project. A limitation of ERIT project was that simulated data were used to develop and test ISAR imaging algorithms. As a natural consequence SPERI Project will try to address the problem of testing ERIT algorithms in presence of real radar data. The following main tasks will be carried out:

  • use ERIT algorithms to produce ISAR images starting from raw real radar data
  • investigate new Super Resolution techniques and test them on real radar data
  • define Automatic Target Recognition (ATR).

The Project will develop and test two ATR chains on ISAR images before and after applying Super Resolution (SR) techniques, with the aim to select the classification approach which will be used for optimize the over-all performance of the radar processor.
The former chain will be based on the whole signature of the imaged target, while the latter on the target features retrieved from ISAR images.
The analysis of ATR performance will be performed to evaluate the impact of ISAR Super Resolution on recognition capabilities of a seeker founder different targets and operating conditions and targets.



Brüggenwirth,; Wagner,; Bieker,; Battisti,; Rispoli,; Greco,; Messina,; Pinelli,; Cataldo,; Martorella,

Signal Processing for Enhanced Radar Imaging (Conference)

European Radar Conference (EuRAD 2018), 2018, (SPERI).