Journal of University of Chinese Academy of Sciences >
Deformation detection approach for repeat-passInSAR based on distributed compressed sensing
Received date: 2015-01-20
Revised date: 2015-04-28
Online published: 2016-01-15
A model for repeat-pass interferometric synthetic aperture radar (InSAR) is proposed to detect deformation based on distributed compressed sensing (DCS). DCS is applied to recover the signals from independent observations of multiple sensors, which are sparse in a transform domain and coherent with each other. We conduct a series of ground-based SAR experiments to compare the recovery performance using different imaging algorithms, such as compressed sensing (CS) and DCS. We find that images recovered by CS and DCS can preserve the phase information of the complex data and have better focus and lower sidelobes than those by Omega-k. Furthermore, by taking advantage of the joint sparsity among multiple scene echoes, DCS joint observation system can further reduce independent observations than CS and achieve scene reconstruction and deformation detection.
TIAN Ye , ZHANG Bingchen , HONG Wen . Deformation detection approach for repeat-passInSAR based on distributed compressed sensing[J]. Journal of University of Chinese Academy of Sciences, 2016 , 33(1) : 107 -114 . DOI: 10.7523/j.issn.2095-6134.2016.01.016
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