Cheney and Borden [1] and Cheney and Nolan [2] have proposed that target identification may be achieved by an analysis of the microlocal structure of their ISAR images. To implement their idea, a Radon transform approach was used [3]. Noise is a problem for the Radon transform and consequently a more robust method against noise is preferable. Candes and Donohoe have investigated the use of the Curvelet transform for Radon data with noise [4] and have shown it to be superior to traditional methods. In this paper, we use simulated ISAR data to investigate the ability of the Curvelet transform to recognize different types of scattering elements in a low signal-to-noise environment.

Date Published: 5 May 2006
PDF: 11 pages
Proc. SPIE 6209, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications III, 620908 (5 May 2006); doi: 10.1117/12.665909

Published in SPIE Proceedings Vol. 6209:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications III
Daniel J. Henry, Editor(s)