DocumentCode :
1890347
Title :
Within the resolution cell: Super-resolution in tomographic SAR imaging
Author :
Zhu, Xiao Xiang ; Bamler, Richard
Author_Institution :
Lehrstuhl fur Methodik der Fernerkundung, Tech. Univ. Munchen, Munich, Germany
fYear :
2011
fDate :
24-29 July 2011
Firstpage :
2401
Lastpage :
2404
Abstract :
We address the problem of resolving two closely spaced complex-valued points from N irregular Fourier domain samples. Although this is a generic super-resolution problem, our target application is SAR tomography where typically the number of acquisitions is N = 10... 100 and SNR = 0 ...10dB. In this paper, a compressive sensing based algorithm is introduced for tomographic SAR inversion. It is named "Scale-down by LI. norm Minimization. Model selection, and Estimation Reconstruction" (SLIMMER, pronounced "slimmer"). SLIMMER combines the advantage of compressive sensing, e.g. high localization accuracy and super-resolution, and the radiometric accuracy of the linear estimator. Moreover, a systematic performance assessment of the SLIMMER algorithm is carried out regarding the elevation estimation accuracy and super-resolution. It is proven that SLIMMER is an efficient estimator; its super resolution factors are in the range of 1.5 to 25 for the aforementioned parameter ranges of TV and SNR. Our results are approximately applicable to nonlinear least-squares estimation, and hence can be considered as fundamental bounds for super-resolution of spectral estimators.
Keywords :
least squares approximations; minimisation; radar imaging; radiometry; synthetic aperture radar; tomography; N irregular Fourier domain samples; SAR tomography; SL1MMER; Scale-down by L1. norm Minimization. Model selection, and Estimation Reconstruction; closely spaced complex-valued points; compressive sensing based algorithm; linear estimator; localization accuracy; nonlinear least-squares estimation; radiometric accuracy; resolution cell; spectral estimators; superresolution; tomographic SAR imaging; Estimation; Signal resolution; Signal to noise ratio; Spatial resolution; Strontium; Tomography; SAR Tomography; SL1MMER; Synthetic Aperture Radar; super-resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
ISSN :
2153-6996
Print_ISBN :
978-1-4577-1003-2
Type :
conf
DOI :
10.1109/IGARSS.2011.6049694
Filename :
6049694
Link To Document :
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