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Proceedings Paper

Evaluation of SAR ATR
Author(s): Arnold C. Williams; Brandy N. Clark
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Paper Abstract

The application and utility of multivariate data analysis techniques to synthetic aperture radar (SAR) automatic target recognizer (ATR) analysis and design is demonstrated on synthetically generated image data sets from the Xpatch scattering prediction code. The multivariate techniques and tools demonstrated include sampling interval estimation, intrinsic dimensionality estimation, nonparametric Bayes error estimation for performance evaluation, and estimation of the number of Gaussian modes that approximate the data sets. The utility of these techniques and tools to SAR ATR analysis and design are elucidated through quantitative results and discussions. The analysis techniques and tools discussed are enhancements of earlier ones that have been successfully applied to data sets consisting of a small number of samples of moderate dimensionality. References are given to those earlier reports that describe these methods, their theory, and earlier results. This paper focuses on the analysis and results of the enhanced methods and tools as applied to SAR data sets consisting of a small number of samples of large dimensionality. A considerable synergy of these combined multivariate statistical tools and image simulation tools is demonstrated. A general and powerful methodology for the quantification and evaluation of SAR ATR designs based upon a combination of these analysis and simulation tools is proposed.

Paper Details

Date Published: 14 June 1996
PDF: 10 pages
Proc. SPIE 2755, Signal Processing, Sensor Fusion, and Target Recognition V, (14 June 1996); doi: 10.1117/12.243194
Show Author Affiliations
Arnold C. Williams, Science Applications International Corp. (United States)
Brandy N. Clark, Science Applications International Corp. (United States)


Published in SPIE Proceedings Vol. 2755:
Signal Processing, Sensor Fusion, and Target Recognition V
Ivan Kadar; Vibeke Libby, Editor(s)

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