SAR tomography employs the multiple-pass data to achieve the elevation location reconstruction of the observation target, while the fully polarimetric data owns rich scattering information. We combine the full-polarimetric data with SAR tomography. By considering the same characteristic of the sparsity of elevation scatters in urban building and the sparse support set in full-polarimetric data, a solution model based on group sparse constraint and sparse constraint, solved by hierarchical sparse method, is proposed. The performance of the method has been compared with those of the single-polarimetric tomography model and the group sparse-based solution method by Monte Carlo simulation experiments. Meanwhile, the method is also applied to semi-simulation of point target experiments based on real data. The results show that the proposed method improves the accuracy of elevation reconstruction and has better robustness, and it accurately recovers the elevation position and backscatter coefficient of the target at low SNR.
YANG Mudan
,
WEI Zhonghao
,
XU Zhilin
,
ZHANG Bingchen
,
HONG Wen
. A full-polarimetric SAR tomography method based on hierarchical sparseness[J]. Journal of University of Chinese Academy of Sciences, 2020
, 37(4)
: 525
-531
.
DOI: 10.7523/j.issn.2095-6134.2020.04.012
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