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Proceedings Paper

Radar target classification using compressively sensed features
Author(s): Ismail Jouny
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Paper Abstract

The paper focuses on extracting scattering centers of radar targets using compressive sensing and using them as features in a target recognition system. It has been shown that a target’s high resolution range profile (HRRP) is sparse in time corresponding to few scatterers that can be associated with target geometry. The recognition system is tested using real radar data of commercial aircraft models. Classification is carried out using distance based and correlation based techniques. Scenarios where the target aspect angle is unknown or known to be within a certain range are also examined.

Paper Details

Date Published: 2 May 2017
PDF: 10 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020019 (2 May 2017); doi: 10.1117/12.2249632
Show Author Affiliations
Ismail Jouny, Lafayette College (United States)

Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)

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