DocumentCode :
3415788
Title :
Compressive sensing for ground penetrating radar imaging based on random filtering
Author :
Cao, YunQian ; Wu, Renbiao ; Liu, Jiaxue ; Lu, XiaoGuang
Author_Institution :
Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China
Volume :
2
fYear :
2011
fDate :
24-27 Oct. 2011
Firstpage :
1898
Lastpage :
1901
Abstract :
Sparse signals can be reconstructed from a small set of measurements basing on the theory of compressive sensing (CS), whereas the key points are the selection of the measurement matrix and the reconstruction algorithm. This paper presents an imaging algorithm for ground penetrating radar based on CS. The measurement matrix is selected via random filters, which can reduce the number of nonzero elements in the measurement matrix effectively. We adopt the simple orthogonal matching pursuit (OMP) algorithm to reconstruct signal with less data storage and lower computational complexity. Simulation results are provided to illustrate the performance of the proposed method.
Keywords :
compressed sensing; ground penetrating radar; radar imaging; signal reconstruction; sparse matrices; compressive sensing; computational complexity; ground penetrating radar imaging algorithm; measurement matrix; nonzero element; orthogonal matching pursuit algorithm; random filtering; sparse signal reconstruction algorithm; Finite impulse response filter; Ground penetrating radar; Image reconstruction; Matching pursuit algorithms; Signal processing algorithms; Compressive Sensing; Ground Penetrating Radar Imaging; Orthogonal Matching Pursuit; Random Filtering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar (Radar), 2011 IEEE CIE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8444-7
Type :
conf
DOI :
10.1109/CIE-Radar.2011.6159945
Filename :
6159945
Link To Document :
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