Article
Engineering, Multidisciplinary
Razieh Darang, Saeed Nasri, Mansoor Zeinali
Summary: This paper presents an iterative approach to minimize phase difference error in interferometric synthetic aperture radar (InSAR) systems. The proposed method describes the interferometric phase relationships, formulates the phase unwrapping problem as an optimization issue, and converts the cost function into a submodular convex Markov random field function. Numerical studies confirm the efficiency and superiority of the proposed method in terms of elevation estimation.
Article
Environmental Sciences
Boyu Liu, Lingda Wu, Xiaorui Song, Hongxing Hao, Ling Zou, Yu Lu
Summary: Synthetic Aperture Radar Interferometry (InSAR) is a rapidly developing remote sensing technique, mainly used in terrain mapping and monitoring. However, the collected phase information in InSAR data inevitably contains noise, making it difficult to obtain the absolute phase from the wrapped phase. This study proposed a deep learning framework (PUnet) for phase unwrapping from InSAR data, which demonstrated high accuracy and robustness in obtaining absolute phases compared to traditional algorithms under various noise levels.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2023)
Article
Geochemistry & Geophysics
Zhiyang Chen, Yuanhao Li, Cong Li, Yan Liu, Xichao Dong, Cheng Hu
Summary: This study models the geometric decorrelation in SAR observation geometry and derives an accurate analytical model. The simulation results confirm the validity of the model. It is found that unparallel tracks introduce an extra geometric decorrelation factor and worsen the geometric decorrelation compared to parallel tracks.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Remote Sensing
Anthony Carpenter, James A. Lawrence, Richard Ghail, Philippa J. Mason
Summary: Interferometric synthetic aperture radar (InSAR) is used to measure Earth surface and structural deformation, and drone InSAR offers improved spatial-temporal data resolutions. This study presents the design, simulation, fabrication, and testing of lightweight and inexpensive copper clad laminate/printed circuit board horn antennas for C-band radar deployed on a drone. The antennas achieved high gain and met the performance criteria, demonstrating the potential of CCL/PCB/FR-4 as a lightweight and inexpensive material for custom antenna production in drone radar and other antenna applications.
Article
Geochemistry & Geophysics
Simon Zwieback, Franz J. Meyer
Summary: The study found pervasive deviations from Gaussianity in repeat-pass radar interferometric data, especially in areas with naturally heterogeneous surfaces. Permanent texture has a significant impact on intensity heterogeneity related to phase heterogeneity. Accounting for heterogeneity has a moderate impact on phase estimates and estimated uncertainty in deformation analyses, but can improve phase estimation accuracy and uncertainty estimates in inherently heterogeneous areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Muhammad Fulki Fadhillah, Arief Rizqiyanto Achmad, Chang-Wook Lee
Summary: In this study, a new algorithm called ICOPS was developed to monitor surface deformation by combining persistent scatterers (PSs) and distributed scatterers (DSs). The algorithm was improved through a machine learning process and showed promising results in terms of accuracy. The advantage of this method is the increased density of measurement points and the spatial clustering information it provides about surface deformation.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Gert Mulder, Freek J. van Leijen, Ramon F. Hanssen
Summary: The observed phase in InSAR products is a combination of various components, including differential topography, line-of-sight displacements, and differential atmospheric delays. Isolating the atmospheric component has been challenging due to its dynamic and superposed nature. In this study, we propose a method to characterize the stochastic properties of atmospheric delays as a means to define the atmospheric signal. By using structure functions, we can describe the spatiotemporal variability of InSAR atmospheric delays and quantify atmospheric noise in deformation time series.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Jun Su Kim, Konstantinos Papathanassiou
Summary: This letter presents an alternative approach for estimating the vertical wavenumber over sloped terrain using range corregistration shifts, which simplifies the calculation effort without compromising the estimation performance. The proposed approach is demonstrated on ALOS PALSAR data and compared against the conventional methodology.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Zegang Ding, Zhen Wang, Yan Wang, Xinnong Ma, Minkun Liu, Tao Zeng, Tiandong Liu
Summary: In this article, a refined multifrequency interferometric synthetic aperture radar phase unwrapping method is proposed for steep terrains. Two main contributions, including steep edge extraction and nonlinear phase model, enhance the accuracy and robustness of phase noise suppression in extremely steep terrain.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geography, Physical
Fengming Hu, Feng Wang, Yexian Ren, Feng Xu, Xiaolan Qiu, Chibiao Ding, Yaqiu Jin
Summary: This paper investigates the error sources of the array-InSAR interferograms and proposes a hybrid 3D phase unwrapping approach for 3D reconstruction. A hypothesis test is developed to identify the phase ambiguity and three indicators are proposed to identify reliable arcs. The L-1 norm approach is used to detect unwrapping errors and a two-tie network strategy is employed for global optimization. Experimental results demonstrate that the proposed algorithm can eliminate errors and provide a viable solution for rapid 3D SAR imaging.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Molly S. Zebker, Jingyi Chen, Marc A. Hesse
Summary: This study presents a method to characterize both surface deformation and tropospheric noise from interferogram subsets. By choosing different subsets of interferograms that use a common-reference SAR scene, tropospheric noise and deformation signals can be quantified. The results show that there is no detectable deformation signal in Oman, while the observed interference phase in Hawaii is mostly associated with tropospheric noise.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Liutong Li, Hong Zhang, Yixian Tang, Chao Wang, Feng Gu
Summary: In this paper, a PhU semantic segmentation model based on gradient information fusion and improved PhaseNet network is proposed to solve the problem of imbalanced classification and error propagation.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Meteorology & Atmospheric Sciences
Yunmeng Cao, Zhiwei Li, Meng Duan, Jianchao Wei
Summary: This study introduces a new method for constructing high-resolution PWV maps by fusing InSAR and GPS measurements to address the issue of InSAR observations being unable to build absolute PWV maps. The method was validated in the Southern California region and showed that the CMVE method significantly outperformed conventional methods in constructing high-resolution PWV maps.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Article
Geochemistry & Geophysics
Yang Lan, Hanwen Yu, Zhihui Yuan, Mengdao Xing
Summary: Phase unwrapping is a key processing step in interferometric synthetic aperture radar (InSAR), and comparing the performance of single-baseline (SB) and multi-baseline (MB) unwrapping methods is important. The two-stage programming approach (TSPA) framework allows for the comparison of SB and MB methods, and this study compares the digital elevation model (DEM) reconstruction accuracy of classical SB methods and their corresponding TSPA-framework-based MB methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Yexian Ren, Aoran Xiao, Fengming Hu, Feng Xu, Xiaolan Qiu, Chibiao Ding, Ya-Qiu Jin
Summary: This study proposes a method to enlarge the baseline aperture restricted by conventional uniform sampling arrays using coprime sampling subarrays, and generates virtual observations by estimating cross-correlation matrices. The newly generated virtual measurements offer better imaging results and the potential to improve imaging without increasing hardware cost.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)