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13 August 1999 Multilook RELAX parametric superresolution and complex HRRR nearest-neighbor target classification
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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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven Robert Stanfill, Jian Li, and Robert L. Williams "Multilook RELAX parametric superresolution and complex HRRR nearest-neighbor target classification", Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999);

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