Article
Geochemistry & Geophysics
Fengming Hu, Feng Wang, Hanwen Yu, Feng Xu
Summary: This study proposes an asymptotic 3-D phase unwrapping algorithm for 3-D reconstruction using sparse array InSAR images. The algorithm improves the reliability of 3-D phase unwrapping and analyzes the possible baseline combinations. The experimental results demonstrate that the proposed method can achieve 3-D reconstruction using only three-pass array InSAR images and optimize baseline design.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
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
Geochemistry & Geophysics
Jonas Kvist Andersen, John Peter Merryman Boncori, Anders Kusk
Summary: DInSAR is a useful technique for measuring ice velocity, but phase unwrapping errors can be a significant source of error. Traditional masking methods are not always effective, so a new method based on pixel connectivity estimation is proposed. The new method can detect the majority of unwrapping errors with a relatively low precision.
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
Engineering, Civil
Benjamin Thomas, Alan Hunter, Samantha Dugelay
Summary: The article introduces an algorithm for detecting and correcting phase wrap errors, improving the accuracy and efficiency of data processing by using the RANSAC algorithm for fine-tuning time delay estimates.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2021)
Article
Geochemistry & Geophysics
Hongyang An, Junjie Wu, Kah Chan Teh, Zhichao Sun, Zhongyu Li, Jianyu Yang
Summary: This article proposes an efficient video formation method for video SAR systems with reduced data, modeling the observed scene as a sum of low-rank and sparse tensors and using a tensor alternating direction method of multiplier. Compared to traditional imaging methods, the proposed approach greatly reduces the amount of data samples.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Hanwen Yu, Ning Cao, Yang Lan, Mengdao Xing
Summary: This article proposes a multisystem interferometric data fusion framework, TSDFF, which combines data from different SAR systems to enhance SAR performance. TSDFF allows datasets from different SAR sensors to help each other, thus expanding the application scope of each sensor.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Maxwell Nogueira Peixoto, Gerhard Krieger, Alberto Moreira, Christian Waldschmidt, Michelangelo Villano
Summary: This paper proposes a method to enhance bistatic SAR interferometer with CubeSats, which can form additional interferograms with small baselines to resolve phase unwrapping errors in digital elevation models (DEMs). Despite the lower quality of CubeSat images, they can be used to detect and resolve phase unwrapping errors without impacting the resolution or accuracy of DEMs. This concept provides a cost-effective solution for generating highly accurate and robust DEMs, and paves the way for distributed SAR interferometric concepts based on CubeSats.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Remote Sensing
Chi Zhang, Zegang Ding, Zehua Dong
Summary: A novel maximum likelihood method based on the migration feature of a moving target in the complex image domain is proposed to estimate the velocity and height of the moving target, which can decrease the computational load and has a smaller estimated error compared to the original method.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Chao Dai, Feng Tian, Zhiyong Suo
Summary: Spaceborne interferometric synthetic aperture radar (InSAR) technology is an effective method for obtaining digital elevation model (DEM) data. The inclined-geosynchronous (InGEO) transmitter with low earth orbit (LEO) receivers (InGEO-LEO) configuration is a novel InSAR system with high resolution, wide swath, and timeliness. However, the conventional Newton iterative method is time-consuming for fast DEM generation in the InGEO-LEO InSAR system. To address this issue, an approximate closed-form solution (ACS) is proposed based on detailed analysis of the bistatic InGEO-LEO geometry, significantly improving the efficiency of geolocation with high precision.
IET RADAR SONAR AND NAVIGATION
(2023)
Article
Geochemistry & Geophysics
Francescopaolo Sica, Sofie Bretzke, Andrea Pulella, Jose-Luis Bueso-Bello, Michele Martone, Pau Prats-Iraola, Maria-Jose Gonzalez-Bonilla, Michael Schmitt, Paola Rizzoli
Summary: Decorrelation phenomena are always present in synthetic aperture radar interferometry, and can provide valuable information about imaged targets. This letter investigates InSAR decorrelation effects at the X-band using data from the TanDEM-X and PAZ spaceborne missions, showcasing the potential of combining bistatic and repeat-pass InSAR acquisitions.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Geochemistry & Geophysics
Hanwen Yu, Xie Hu
Summary: This article proposes a novel knowledge-aided PU (KAPU) approach that compiles different prior knowledge from different sources with InSAR observations through an integer programming model. The mathematical proof demonstrates that the constraint of the optimization model of KAPU is totally unimodular, allowing KAPU to be efficiently solved without the constraint that the ambiguity number is an integer. Theoretical analysis and extensive experimental results show that KAPU outperforms existing model-based 2-D InSAR PU algorithms in DEM generation and surface deformation estimation.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Wei Zhao, Cai Wen, Quan Yuan, Rong Zheng
Summary: In this article, an efficient imaging method based on robust sparse array synthesis (SAS) is proposed, which can achieve image quality comparable to that of the backprojection algorithm (BPA), but with a substantial reduction in computational time up to 90%. The method conducts range-dimension matched filtering and azimuth-dimension matched filtering using a selected sparse aperture and filtering weights, and introduces robust constraints on the filter design.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
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
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)