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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Three-Dimensional Structural Parameter Inversion of Buildings by Distributed Compressive Sensing-Based Polarimetric SAR Tomography Using a Small Number of Baselines
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Three-Dimensional Structural Parameter Inversion of Buildings by Distributed Compressive Sensing-Based Polarimetric SAR Tomography Using a Small Number of Baselines

机译：基于少量基线的基于分布压缩感知的极化SAR层析成像的三维三维结构参数反演

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摘要

An important condition for urban studies is quantitative acquisition of spatial information, e.g., three-dimensional (3-D) structural parameters of buildings. Synthetic aperture radar tomography (TomoSAR) provides scene reflectivity estimation along azimuth, range, and elevation coordinates. For a small number of acquisitions and their irregular spacing, however, the common Fourier-based 3-D SAR-focusing approaches, even compressive sensing (CS)-based methods, bring about some imaging quality problems. This paper addresses the 3-D imaging of buildings based on the framework of CS using fully polarimetric (FP) multibaseline SAR interferometric (MB-InSAR) tomography at C-band. In this paper, we propose a new distributed CS-based FP MB-InSAR tomography method (FP-DCS TomoSAR method), which is a new polarimetric spectral analysis method based on distributed compressive sensing (DCS), model order selection, and maximum-likelihood parameter estimation for 3-D structural parameter reconstruction. Compared to the CS method, the FP-DCS TomoSAR method takes advantage of the intersignal correlations between neighboring azimuth-range pixels as well as between polarimetric channels to attain higher superresolution imaging and elevation estimation accuracy. Numerical results on simulated and real data validate the effectiveness of this novel technique by using FP C-band data acquired by Radarset-2 and are compared with the FP noise subspace fitting estimator.
机译：城市研究的重要条件是对空间信息的定量获取，例如建筑物的三维（3-D）结构参数。合成孔径雷达层析成像（TomoSAR）提供沿方位角，范围和仰角坐标的场景反射率估计。但是，对于少量的采集及其不规则的间隔，基于傅立叶的常见3-D SAR聚焦方法，甚至基于压缩传感（CS）的方法，都会带来一些成像质量问题。本文使用C波段全极化（FP）多基线SAR干涉测量（MB-InSAR）层析成像技术，基于CS框架解决了建筑物的3D成像问题。在本文中，我们提出了一种新的基于CS的分布式FP MB-InSAR层析成像方法（FP-DCS TomoSAR方法），这是一种基于分布式压缩感测（DCS），模型阶数选择和最大- 3-D结构参数重建的似然参数估计。与CS方法相比，FP-DCS TomoSAR方法利用相邻方位范围像素之间以及极化通道之间的信号间相关性来获得更高的超分辨率成像和高程估计精度。模拟和真实数据的数值结果通过使用Radarset-2采集的FP C波段数据验证了该新技术的有效性，并与FP噪声子空间拟合估计器进行了比较。

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