Title :
Feature extraction of a single dihedral reflector from SAR data
Author :
Liu, Zheng-She ; Li, Jian
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
Abstract :
As one of the key steps in the feature extraction of targets consisting of both trihedral and dihedral corner reflectors via synthetic aperture radar, this paper studies the problem of estimating the parameters of a single dihedral corner reflector. The data model of the problem and the Cramer-Rao bounds (CRBs) for the parameter estimates of the data model are presented. Two algorithms, the FFTB (fast Fourier transform based) algorithm and the NLS (non-linear least squares) algorithm, are devised to estimate the model parameters. Numerical examples show that the parameter estimates obtained with both algorithms approach the CRBs as the signal-to-noise ratio increases. The parameter estimates obtained with the NLS algorithm start to achieve the CRB at a lower SNR than those with the FFTB algorithm, while the latter algorithm is computationally more efficient
Keywords :
electromagnetic wave reflection; fast Fourier transforms; feature extraction; least squares approximations; parameter estimation; radar cross-sections; synthetic aperture radar; CRB; Cramer-Rao bounds; FFT algorithm; NLS algorithm; RCS; SAR data; automatic target classification; computationally efficient algorithm; data model; dihedral corner reflector; fast Fourier transform; feature extraction; nonlinear least squares; parameter estimation; point scatterers; signal to noise ratio; synthetic aperture radar; Data engineering; Data models; Fast Fourier transforms; Feature extraction; Least squares approximation; Parameter estimation; Radar cross section; Radar scattering; Signal to noise ratio; Synthetic aperture radar;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.604856