基于二维变分模分解的干涉相位去噪增强Goldstein滤波器

Rahul Dasharath Gavas;Soumya Kanti Ghosh;Arpan Pal
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引用次数: 0

摘要

干涉图的去噪是合成孔径雷达(InSAR)数据处理的重要步骤。主要目标是在保留干涉图条纹的同时,尽可能地过滤噪声。在广泛可用的滤波器类别中,频域滤波器仍在使用,因为它们对不同相位噪声特性具有鲁棒性和可推广性。本文讨论了对众所周知的频域滤波器的增强,即Goldstein滤波器,它基本上是干涉产品的相位滤波算法。对Goldstein滤波器提出的扩展处理基于空间频率模式导出调谐参数。这是通过使用变分模式分解(2D-VMD)的二维版本在被测干涉图上呈现的模式级特性来实现的。仿真结果和实际干涉图数据表明,该方法在降低噪声的同时最大限度地减少了信号损耗。
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Enhanced Goldstein Filter for Interferometric Phase Denoising Using 2-D Variational Mode Decomposition
Denoising of interferograms is a vital step in the processing of synthetic aperture radar (InSAR) data. The primary goal is to filter the noise to the extent possible while retaining the fringes of the interferograms. Among the widely available classes of filters, the frequency-domain filters are still being used, owing to their robustness and generalizability to varying phase noise characteristics. This article deals with an enhancement to the well-known frequency-domain filter, i.e., the Goldstein filter, which is basically a phase filtering algorithm for interferometric products. The proposed extension to the Goldstein filter deals with deriving the tuning parameter based on the spatial frequency modes. This is achieved by using the mode-level characteristics rendered by the 2-D version of variational mode decomposition (2D-VMD) on the interferograms under test. The results of simulation and real interferogram data show that the proposed approach reduces the noise levels while minimizing the loss of signal.
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