Kurt W. Knurr

Date of Award


Document Type


Degree Name

Master of Science


Department of Electrical and Computer Engineering

First Advisor

Byron M. Welsh, PhD


This study investigated methods of targets detection using Wide-Angle Synthetic Aperture Radar (WASAR). WASAR uses multiple aspect angle Synthetic Aperture Radar (SAR) images of the same scene. The SAR images were generated using a pre-release software package from package from Loral Corporation. The software was able to generate 512 by 512 pixel SAR images that contained various vegetation return which for our purposes we classified as clutter. Within this clutter, targets (M35 trucks) could be placed at random location and orientations. The software also had the capability of generating fully- polarimetic WASAR images with multiple depression angles. This data was then processed and various detection algorithms tested to exploit the amount and diversity of information available from the multiple images. SAR images are generally known to contain large amounts of data and WASAR images contain even more due to the multiple images. Various pre-processing filters were analyzed for detection optimization. These filters included: polarimetric averaging, polarimetric span, polarimetric optimal weighting, and polarimetric whitening filters. Simple classical detection (thresholding) algorithms were evaluated using these preprocessed data sets. The use of WASAR imagery improved detection by allowing thresholds to be set higher than for simple SAR thereby avoiding false alarms yet still allowing detection of the known targets.

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