15 September 1998 Automatic target recognition using Eigen templates
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Abstract
This paper presents ATR results with High Range Resolution (HRR) profiles used for classification. It is shown that effective HRR-ATR performance can be achieved if the templates are formed via Singular Value Decomposition (SVD) of detected HRR profiles. It is demonstrated theoretically that in the mean-squared sense, the eigen-vectors represent the optimal feature set. SVD analysis of a large class of XPATCH and MSTAR HRR-data clearly indicates that significant proportion (> 90%) of target energy is accounted for by the eigen-vectors of range correlation matrix, corresponding to only the largest singular value. The SV Decomposition also decouples the range and angle basis spaces. Furthermore, it is shown that significant clutter reduction can be achieved if HRR data is reconstructed using only the significant eigenvectors. ATR results with eigen-templates are compared with those based on mean-templates. Results are included for both XPATCH and MSTAR data using linear least- squares and matched-filter based classifiers.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arnab Kumar Shaw, Arnab Kumar Shaw, Vijay Bhatnagar, Vijay Bhatnagar, } "Automatic target recognition using Eigen templates", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321871; https://doi.org/10.1117/12.321871
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