作者:Wei, LH (Wei, Lianhuan); Balz, T (Balz, Timo); Zhang, L (Zhang, Lu); Liao, MS (Liao, Mingsheng)

卷:12 期:6 页:1377-1381 DOI:10.1109/LGRS.2015.2402124 出版年:JUN 2015

摘要:As an advanced technique, synthetic aperture radar (SAR) tomography makes it possible to overcome the layover problem induced by the intrinsic side-looking geometry of SAR sensors. However, traditional nonparametric spectral estimators, e.g., truncated singular value decomposition, are limited by their poor elevation resolution. On the other hand, the compressive-sensing-based approaches using the basis-pursuit strategy to find an L1-norm minimization solution for SAR tomography (TomoSAR) are extremely time consuming. Therefore, a fast and robust tomographic algorithm with super-resolution capability is needed. In this letter, we propose a new approach for TomoSAR based on two-step iterative shrinkage/thresholding (TWIST). TWIST uses a two-step strategy to speed up the L1-norm minimization procedure and can achieve an exceptionally fast convergence speed for TomoSAR. Experimental studies with simulated signals and a spotlight-mode TerraSAR-X data set were carried out to demonstrate the merits of the proposed TWIST approach in terms of robustness, fast convergence speed, and super-resolution capability.

地址:[Wei, Lianhuan] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.

Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China.

通讯作者地址:Wei, LH (通讯作者),Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.

电子邮件地址:lianhuan@whu.edu.cn; balz@whu.edu.cn; luzhang@whu.edu.cn; liao@whu.edu.cn