Target identification using fractional Fourier features

Ismail I. Jouny

doi:10.1117/12.543065

21 September 2004 Target identification using fractional Fourier features

Ismail I. Jouny

Proceedings Volume 5426, Automatic Target Recognition XIV; (2004) https://doi.org/10.1117/12.543065
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

This paper focuses on non-cooperative automatic target recognition via features extracted from the radar backscatter returns using the Fractional Fourier Transform. This study is motivated by two factors: first, to examine radar backscatter mechanism of standard small targets, and second, to extract pertinent scattering features that can be used in target recognition. Radar returns have been examined using time-frequency analysis techniques, particularly those targets with dispersive scattering behavior. The Fractional Fourier Transform provides an attractive alternative to time-frequency analysis. The motivation lies in the fact that fractional Fourier Transform features retain phase information, and, because of their linear structure, are potentially less susceptible to noise contamination compared to their time-frequency counterparts. The fractional Fourier Transform has its disadvantages as well which are addressed in this paper. The FrFT scattering analysis scheme is tested using real radar signatures of commercial aircraft recorded in the UHF range.

Citation Download Citation

Ismail I. Jouny "Target identification using fractional Fourier features", Proc. SPIE 5426, Automatic Target Recognition XIV, (21 September 2004); https://doi.org/10.1117/12.543065

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available