A Novel Method for Airborne Array-InSAR Tomography Based on Off-Grid Target Modeling and Group Sparsity

Qichang Guo;Xingdong Liang;Yanlei Li;Yujie Dai
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引用次数: 0

Abstract

Airborne array interferometric synthetic aperture radar (array-InSAR) tomography is an effective method for obtaining 3-D point clouds on the ground. However, the quality of point clouds is limited by multiple factors, such as phase noise, reconstruction algorithm, and so on. In this letter, the problem of point cloud stratification is discussed. To solve this problem, the authors propose a novel method. First, the interference phase between multichannel images is filtered to suppress the phase noise. Then, an elevation reconstruction algorithm based on off-grid target modeling and group sparsity is carried out, which can solve the mismatch problem of the target. In the final part, the effectiveness of the proposed method is validated using airborne array-InSAR data from the Sichuan province, China.
基于离网目标建模和组稀疏性的机载阵列-InSAR 层析成像新方法
机载阵列干涉合成孔径雷达(array-InSAR)层析成像是获取地面三维点云的有效方法。然而,点云的质量受到多种因素的限制,如相位噪声、重建算法等。本信讨论了点云分层问题。为解决这一问题,作者提出了一种新方法。首先,过滤多通道图像之间的干扰相位以抑制相位噪声。然后,基于离网目标建模和组稀疏性的高程重建算法可以解决目标的不匹配问题。最后,利用中国四川省的机载阵列-InSAR 数据验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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