Paper
5 June 1995 Target prescreening based on 2D gamma kernels
Jose C. Principe, Alex Radisavljevic, Munchurl Kim, John W. Fisher III, Margarita Hiett, Leslie M. Novak
Author Affiliations +
Abstract
This work develops and tests a new target prescreening algorithm based on 2D gamma kernels. The key feature of the new kernel set is the existence of a free parameter that determines the size of its region of support. We show that the scale affects the false alarm rate of the two parameter CFAR test. We also show that a linear discriminant funtion composed from the linear and quadratic terms of the intensity in the test cell neighborhood improves the false alarm rate when compared with the two parameter CFAR.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jose C. Principe, Alex Radisavljevic, Munchurl Kim, John W. Fisher III, Margarita Hiett, and Leslie M. Novak "Target prescreening based on 2D gamma kernels", Proc. SPIE 2487, Algorithms for Synthetic Aperture Radar Imagery II, (5 June 1995); https://doi.org/10.1117/12.210842
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Sensors

Detection and tracking algorithms

Target detection

Synthetic aperture radar

Automatic target recognition

Algorithm development

Filtering (signal processing)

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