Date of Award


Document Type


Degree Name

Master of Science in Electrical Engineering


Department of Electrical and Computer Engineering

First Advisor

Andrew J. Terzuoli, PhD


This research details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips containing targets and non-targets are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution. Spatial resolution is reduced by lowering the pixel count or synthesizing a degraded image by filtering and reducing the pixel count. A two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three feature sets, size, contrast, and texture, are used to train a linear classifier and to estimate probability density functions for the two classes. The results are scored using Area Under the Receiver Operating Characteristic (AUROC) curve. The CFAR detector is shown to perform better at a lower resolution. All three feature sets perform well together with degradation of resolution; separately the sets have different performances. The texture features perform the best because they do not depend on the number of pixels on the target; the size features perform the worst for the same reason. The contrast features yield improved performance when the resolution is slightly reduced.

AFIT Designator


DTIC Accession Number