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International Conference on Computer Graphics, Imaging and Visualization (CGIV'05)
Super-Resolution SAR Imaging via Nonlinear Regressive Model Parameter Estimation Method
Beijing, China
July 26-July 29
ISBN: 0-7695-2392-7
ASCII Text
x 
 
Xiong-liang Wang, Zheng-ming Wang, "Super-Resolution SAR Imaging via Nonlinear Regressive Model Parameter Estimation Method," Computer Graphics, Imaging and Visualization, International Conference on, pp. 67-72, International Conference on Computer Graphics, Imaging and Visualization (CGIV'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/CGIV.2005.72,
author = {Xiong-liang Wang and Zheng-ming Wang},
title = {Super-Resolution SAR Imaging via Nonlinear Regressive Model Parameter Estimation Method},
journal ={Computer Graphics, Imaging and Visualization, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2392-7},
pages = {67-72},
doi = {http://doi.ieeecomputersociety.org/10.1109/CGIV.2005.72},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer Graphics, Imaging and Visualization, International Conference on
TI - Super-Resolution SAR Imaging via Nonlinear Regressive Model Parameter Estimation Method
SN - 0-7695-2392-7
SP67
EP72
A1 - Xiong-liang Wang,
A1 - Zheng-ming Wang,
PY - 2005
KW - null
VL - 0
JA - Computer Graphics, Imaging and Visualization, International Conference on
ER -
 
Xiong-liang Wang, National University of Defense Technology - China
Zheng-ming Wang, National University of Defense Technology - China
A novel SAR super-resolution imaging method is described. Firstly, SAR image peak extraction is carried out in the image domain and the coarse feature parameter estimation is obtained. Secondly, Parameter estimation of nonlinear regressive model is carried out in the phase history domain and the fine feature parameter estimation is obtained. Finally, from the estimated parameter and based on the point-scattering model, the simulated phase history data of large dimensions is generated. By FFT imaging, higher resolution image is obtained. Experimental examples have shown that this method offer significant advantages over the FFT methods to better resolve the dominant target scatterers.
Citation:
Xiong-liang Wang, Zheng-ming Wang, "Super-Resolution SAR Imaging via Nonlinear Regressive Model Parameter Estimation Method," cgiv, pp.67-72, International Conference on Computer Graphics, Imaging and Visualization (CGIV'05), 2005
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