DocumentCode :
326488
Title :
1-D feature extraction using a dispersive scattering center parametric model
Author :
Fuller, D.F. ; Terzuoli, A.J. ; Collins, P.J. ; Williams, R.
Author_Institution :
Inst. of Technol., Wright-Patterson AFB, OH, USA
Volume :
2
fYear :
1998
fDate :
21-26 June 1998
Firstpage :
1296
Abstract :
Automatic object recognition, the ability for a machine to classify an object it has detected, is an area of continual interest. The classification of objects requires extraction of discriminatory information, and this process is called feature extraction. The extractable features are inextricably tied to the type of sensor used, and this work addresses one-dimensional, high resolution radar (HRR). Several approaches have been proposed for feature extraction in HRR. One approach is based on finding sinusoids in noise by a sum-of-damped exponentials (DE) model. The features of the DE-based scattering models, range and amplitude, have been used for feature extraction, but the DE model simplistically assumes that all scattering centers on the object have the frequency response of an ideal point scatterer. The high potential improvement to the damped exponential model lies in estimating the frequency response of each scattering center uniquely. This improvement is based on the geometric theory of diffraction of (GTD) and the uniform theory of diffraction (UTD) and includes electromagnetic scattering theory as a basis for scattering center modeling. Research in adapting the DE models to include GTD/UTD has been performed, but has had limited implementation in object recognition problems. This work provides an analysis and a proof-of-concept for implementing the GTD/UTD-based dispersive scattering center (DSC) model to perform object recognition. The DSC model presented is based directly upon Potter´s (see IEEE Trans. Antennas Progagat., vol.43, p.1058-67, 1995) work at the Ohio State University.
Keywords :
electromagnetic wave scattering; feature extraction; geometrical theory of diffraction; image classification; image resolution; object recognition; radar resolution; 1D feature extraction; DE-based scattering models; GTD; UTD; amplitude; automatic object recognition; dispersive scattering center parametric model; electromagnetic scattering theory; feature extraction; frequency response; geometric theory of diffraction; high resolution radar; ideal point scatterer; noise; object classification; range; sinusoids; sum-of-damped exponentials model; uniform theory of diffraction; Data mining; Dispersion; Electromagnetic scattering; Feature extraction; Frequency response; Object detection; Object recognition; Physical theory of diffraction; Radar detection; Radar scattering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Antennas and Propagation Society International Symposium, 1998. IEEE
Conference_Location :
Atlanta, GA, USA
Print_ISBN :
0-7803-4478-2
Type :
conf
DOI :
10.1109/APS.1998.702190
Filename :
702190
Link To Document :
بازگشت