BUILDING RECONSTRUCTION BASED ON A SMALL NUMBER OF TRACKS USING NONPARAMETRIC SAR TOMOGRAPHIC METHODS

Nowadays, the synthetic aperture radar (SAR) tomography (TomoSAR) technique plays a notable role in the 3D reconstruction of urban buildings through several SAR acquisitions with slightly different positions. Nonparametric-based TomoSAR spectral estimation algorithms usually work well when a large number of SAR observations. In this study, with a limited number of SAR images, we have assessed the efficiency of the nonparametric spectral estimation methods, including maximum entropy (ME), singular value decomposition (SVD), linear prediction (LP), Capon, minimum norm (MN), and beamforming (BF) in the reconstruction of the third dimension of urban buildings. The experiments are conducted on both simulated and TerraSAR-X stripmap images to indicate the effectiveness of the LP proposed estimation algorithm. The analysis of the results proves that by minimizing the average output signal power over the antenna array elements, the LP spectral estimation achieves the discrimination of distinct scatterers inside an image pixel. In addition, this low computational estimator improves the sidelobe suppression and the height estimates of the scatterers in the complex multiple-scattering urban environment. Compared to SVD, maximum entropy, Capon, minimum norm, and beamforming, the height of the Eskan tower in Tehran, Iran, obtained with the LP technique, is considerably near to field-based measurement

TerraSAR-X StripMap Data Interpretation of Complex Urban Scenarios with 3D SAR Tomography

The severe layover problem of complex urban scenarios in SAR data makes SAR data interpretation very difficult, especially for nonexperts. In this paper, we use 3D SAR tomography for SAR data interpretation of dense urban areas. An efficient and robust approach named Butterworth-filter based singular value decomposition (BSVD) is used for tomographic analysis. Two typical dense urban areas of interest located in Shanghai are analyzed. The tomographic results could help users to better understand the backscattering scenario. The experimental results indicate that SAR tomography is a promising and effective way to facilitate SAR data interpretation of complex urban areas