Accession Number : ADA335655
Title : A Dispersive Scattering Center, Parametric Model for 1-D ATR
Descriptive Note : Master's thesis
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH SCHOOL OF ENGINEERING
Personal Author(s) : Fuller, Dane F.
PDF Url : ADA335655
Report Date : DEC 1997
Pagination or Media Count : 66
Abstract : The dispersive scattering center (DSC) model characterizes high-frequency backscatter from radar targets as a finite sum of localized scattering geometries distributed in range, these geometries, along with their relative locations, can be conveniently used as features in a one-dimensional automatic target recognition (ATR) algorithm. The DSC model's type and range parameters correspond to geometry and distance features according to the geometric theory of diffraction (GTD). Since these parameters are estimated in the phase history domain of the radar signal, the range parameter does provide superresolution in the time domain. To demonstrate the viability of feature extraction based on the DSC model's range and type parameters, a four class ATR experiment was performed. The experimental data contains 301 direct range measurements each for four model aircraft of similar size and shape at 0 degrees elevation and from 0 to 30 degrees azimuth. After implementing DSC model feature extraction on this data, a fully-connected, two-layer neural net obtained over 98% classification accuracy. In addition, DSC model feature extraction offers an approximate 85% reduction in the number of features compared to the numerous Fourier bin magnitudes in template matching approaches to ATR.
Descriptors : *NEURAL NETS, *TARGET RECOGNITION, *RADAR SIGNALS, ALGORITHMS, ONE DIMENSIONAL, THESES, SYNTHETIC APERTURE RADAR, BACKSCATTERING, HIGH RESOLUTION, RADAR TARGETS, AIRCRAFT MODELS, TARGET CLASSIFICATION, FEATURE EXTRACTION.
Subject Categories : Cybernetics
Active & Passive Radar Detection & Equipment
Distribution Statement : APPROVED FOR PUBLIC RELEASE