Date of Award

3-2004

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Steven C. Gustafson, PhD

Abstract

High Range Resolution (HRR) radar profiles map three-dimensional target characteristics onto one-dimensional signals that represent reflected radar intensity along target extent. In this thesis, second through fourth statistical moments are extracted from HRR profiles and input to Fisher Linear Discriminant (FLD) classifiers. An iterative classification process is applied that gradually minimizes required a priori knowledge about the target data. It is found that the second through fourth statistical moments of HRR profiles are useful features in the FLD classification of dissimilar targets and they provide reasonable discrimination of similar targets. Greater than 69% correct classification for two-target scenarios and greater than 60% correct classification for three-target scenarios is obtained using a single HRR profile extracted from a full 360-degree aspect angle window. A key contribution of this thesis is the demonstration that simple statistical moment features and simple linear classifiers can be used to effectively classify HRR profiles.

AFIT Designator

AFIT-GE-ENG-04-06

DTIC Accession Number

ADA426573

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