SAR tomography of forested areas: An APES-based virtual beamforming approach

G. Martín del Campo, Y. Shkvarko, K. Lukin, A. Reigber
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Abstract

The main purpose of synthetic aperture radar tomography (T-SAR) is to retrieve the vertical distribution of the backscattered power within a range-azimuth resolution cell, allowing three dimensional (3-D) imaging of volumetric targets. The achievable resolution of conventional spectral estimators, used to tackle with the T-SAR vertical distribution estimation problem, highly depends on the span of the tomographic aperture and on the number of acquisitions, reason why, adaptive spectral estimators were introduced in order to ease such limitations. This paper proposes a novel amplitude and phase estimation (APES) -based virtual beamforming approach aimed at resolution enhanced SAR tomography of forested areas, which functions properly using only a few passes and arbitrary constellation geometries, and with imaging capabilities comparable to those gotten from super-resolution compressed sensing spectral estimators with the sum of Kronecker products decomposition technique as a pre-processing step.
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森林地区的SAR层析成像:基于apes的虚拟波束形成方法
合成孔径雷达层析成像(T-SAR)的主要目的是在距离-方位分辨率单元内检索后向散射功率的垂直分布,从而实现体目标的三维成像。用于解决T-SAR垂直分布估计问题的传统光谱估计器的可实现分辨率在很大程度上取决于层析孔径的跨度和采集的数量,因此引入自适应光谱估计器以缓解这种限制。本文提出了一种新的基于幅度相位估计(APES)的虚拟波束形成方法,用于森林地区的分辨率增强SAR层析成像,该方法仅使用少量通道和任意星座几何形状即可正常工作,其成像能力可与采用Kronecker积和分解技术作为预处理步骤的超分辨率压缩感知光谱估计器相媲美。
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