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Proceedings Paper

Multilook RELAX parametric superresolution and complex HRRR nearest-neighbor target classification
Author(s): Steven Robert Stanfill; Jian Li; Robert L. Williams
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Paper Abstract

Target classification using an adjusted relative phase MSE nearest neighbor classifier and multi-look RELAX measures will be studied. This approach is a significant modification to the standard MSE nearest neighbor classifiers that are currently being used. Complex train and test signature similarities are amplified via a multi-look RELAX algorithm to obtain features consistent with point scatterer parametric models. The parameters are then used to simulate phase histories to various lengths. Transformation to the range domain at original and improved resolutions and adjustment of relative phase to a minimum completes the final data preparation to input into a nearest neighbor MSE classifier. Significant classification performance gains over the baseline MSE classifier is observed and graphically illustrated.

Paper Details

Date Published: 13 August 1999
PDF: 9 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357654
Show Author Affiliations
Steven Robert Stanfill, Univ. of Florida (United States)
Jian Li, Univ. of Florida (United States)
Robert L. Williams, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

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