Paper Info
Title
Sar Tomography Imaging Based On Generalized Orthogonal Matching Pursuit-The Case Study Of Pangu 7 Star Hotel In Beijing
Abstract
Compressive sensing theory can recover the original signal from little observation data, by means of the non-adaptive measurement far below Nyquist sampling and the optimization method. Due to the number of track is limited and the uneven distribution of tracks, the traditional method is difficult to image effectively in the practical application, while the compressive sensing theory by tomoSAR three-dimensional imaging (MUSIC, APES, etc.) can solve the problem easily, and it can realize high resolution imaging of SAR in the height direction. This paper applied the Generalized Orthogonal Matching Pursuit (GOMP) algorithm to the SAR tomography imaging, which can accurately reconstruct the signal in the height direction. Meanwhile, in this paper, 14 images of ascend track from which is "TerraSAR-X" HH polarization mode in Beijing during the period of 2011-2014 were taken as the test data, and Beijing pangu7 star hotel is taken as the research target. Finally, the result indicates that our algorithm is better than typical Orthogonal Matching Pursuit (OMP) algorithm.
Year
DOI
Venue
2016
10.1109/IGARSS.2016.7730740
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
Keywords
Field
DocType
synthetic aperture radar, tomography imaging, compressive sensing, generalized orthogonal matching pursuit
Matching pursuit,Computer vision,Synthetic aperture radar,Computer science,Remote sensing,Tomography,Artificial intelligence,Test data,Nyquist–Shannon sampling theorem,Image resolution,Beijing,Compressed sensing
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
4
8
Name
Order
Citations
PageRank
Shuguang He101.01
Lei Pang200.68
Xuedong Zhang301.01
Hui Liu411.72
Hui Bi500.34
Liping Ai601.01
Mengxin Sun701.01
Yong Wang800.68