Date of Award
Master of Science in Electrical Engineering
Department of Electrical and Computer Engineering
Julie A. Jackson, PhD.
ATR requires detecting and estimating distinguishing characteristics of a target of interest. Radar data provides range and amplitude information; range distinguishes location relative to the radar whereas amplitude determines strength of reflectivity. Strong reflecting scattering features of targets are detected from a combination of radar returns, or radar PH data. Strong scatterers are modeled as canonical shapes (a plate, dihedral, trihedral, sphere, cylinder, or top-hat). Modeling the scatterers as canonical shapes takes the high dimensional radar PH from each scatterer and parameterizes the scatterer according to its location, size, and orientation. This thesis e ciently estimates the parameters of canonical shapes from radar PH data using dictionary search. Target scattering peaks are detected using 2-D SAR imaging. The parameters are estimated with decreased computation and improved accuracy relative to previous algorithms through reduced SAR image processing, informed parameter subspace bounding, and more e cient dictionary clustering. The effects of the collection fight path and radar parameters are investigated to permit pre-collection error analysis. The results show that even for a limited collection geometry, the dictionary estimates the canonical shape scatterer parameters well.
DTIC Accession Number
Crosser, Matthew P., "Improved Dictionary Formation and Search for Synthetic Aperture Radar Canonical Shape Feature Extraction" (2014). Theses and Dissertations. 593.