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Proceedings Paper

Multiresolution order-statistic CFAR techniques for radar target detection
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Paper Abstract

Order-Statistic Constant False-Alarm Rate (OS-CFAR) processing provides an adaptive threshold to distinguish targets from clutter returns in radar detection. In traditional OS-CFAR, ordered statistics from a fixed-size reference window surrounding the cell under test (CUT) provide an estimate of the mean clutter power. We investigate adapting the reference window size as a function of the observed data in order to obtain robust detection performance in nonhomogeneous clutter environments. Goodness-of-fit tests are used to select the adaptive reference window size. Unlike traditional OS-CFAR, computationally e±cient multiscale OS-CFAR based on this approach must be modified to include the CUT in the reference window. The effects of CUT inclusion are investigated. Preliminary results suggest that CUT-inclusive OS-CFAR with adaptive window size performs well in nonhomogeneous clutter environments of varying size. These results point to the feasibility of computationally efficient multi-scale OS-CFAR.

Paper Details

Date Published: 11 March 2005
PDF: 11 pages
Proc. SPIE 5674, Computational Imaging III, (11 March 2005); doi: 10.1117/12.600577
Show Author Affiliations
Michael F. Rimbert, Purdue Univ. (United States)
Mark R. Bell, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 5674:
Computational Imaging III
Charles A. Bouman; Eric L. Miller, Editor(s)

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