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Proceedings Paper

Two-beam coupling correlation synthetic aperture radar image recognition with power-law scattering centers pre-enhancement
Author(s): Bahareh Haji-saeed; Jed Khoury; Charles L. Woods; John Kierstead
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Paper Abstract

Synthetic radar image recognition is an area of interest for military applications including automatic target recognition, air traffic control, and remote sensing. Here a dynamic range compression two-beam coupling joint transform correlator for detecting synthetic aperture radar (SAR) targets is utilized. The joint input image consists of a pre-power-law, enhanced scattering center of the input image and a linearly synthesized power-law enhanced scattering center template. Enhancing the scattering center of both the synthetic template and the input image furnishes the conditions for achieving dynamic range compression correlation in two-beam coupling. Dynamic range compression: (a) enhances the signal to noise ratio, (b) enhances the high frequencies relative to low frequencies, and (c) converts the noise to high frequency components. This improves the correlation peak intensity to the mean of the surrounding noise significantly. Dynamic range compression correlation has already been demonstrated to outperform many optimal correlation filters in detecting signals in severe noise environments. The performance is evaluated via established metrics, such as peak-to-correlation energy (PCE), Horner efficiency and correlation peak intensity. The results showed significant improvement as the power increased.

Paper Details

Date Published: 17 March 2008
PDF: 10 pages
Proc. SPIE 6973, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2008, 69730I (17 March 2008); doi: 10.1117/12.777652
Show Author Affiliations
Bahareh Haji-saeed, Solid State Scientific Corp. (United States)
Jed Khoury, Air Force Research Lab./SNHC (United States)
Charles L. Woods, Air Force Research Lab./SNHC (United States)
John Kierstead, Solid State Scientific Corp. (United States)

Published in SPIE Proceedings Vol. 6973:
Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2008
William J. Tolone; William Ribarsky, Editor(s)

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