Phase Estimation for Distributed Scatterers by Alternating Projection

Ruya Xiao;Xiufeng He;Zhuang Gao;Fengyu Yao
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引用次数: 1

Abstract

Decorrelation is a major obstacle to the application of multitemporal interferometric synthetic aperture radar (InSAR) in areas with low coherence. Distributed scatterers (DSs) with similar backscattering in the spatial neighborhood are the key to improving the observational density and accuracy of deformation estimation in fast decorrelation regions. Phase series estimation from all possible interferograms is expected to improve the signal-to-noise ratio (SNR) and further enhance the sensitivity of deformation measurement. The coherence bias and the efficiency of the phase estimation raise concerns. In this article, we propose a computationally attractive algorithm for the interferometric phase estimation, namely alternating projection (AP), which is a combination of the alternating maximization and the projection matrix decomposition methods. The homogenous pixel selection and coherence estimation bias correction are conducted by the FaSHPS algorithm and DSIpro software toolbox. Results of simulations and real SAR data show that the proposed AP method could reconstruct credible phase series comparable to the quasi-Newton optimization algorithm [Broyden–Fletcher–Goldfarb–Shanno (BFGS)] while having three times the efficiency gain.
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基于交替投影的分布式散射体相位估计
去相关是影响多时相干涉合成孔径雷达(InSAR)在低相干区域应用的主要障碍。在空间邻域具有相似后向散射的分布散射体是提高快速去相关区域观测密度和形变估计精度的关键。对所有可能的干涉图进行相位序列估计,有望提高信噪比,进一步提高变形测量的灵敏度。相位估计的相干偏差和效率问题引起了人们的关注。本文提出了一种计算上有吸引力的干涉相位估计算法,即交替投影(AP),它是交替最大化和投影矩阵分解方法的结合。利用FaSHPS算法和DSIpro软件工具箱进行均匀像素选择和相干估计偏差校正。仿真结果和实际SAR数据表明,该方法可以重建与准牛顿优化算法[Broyden-Fletcher-Goldfarb-Shanno (BFGS)]相当的可信相位序列,而效率增益是准牛顿优化算法的3倍。
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2024 Index IEEE Journal on Miniaturization for Air and Space Systems Vol. 5 Table of Contents Front Cover The Journal of Miniaturized Air and Space Systems Broadband Miniaturized Antenna Based on Enhanced Magnetic Field Convergence in UAV
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