Efficient method for outlier removal in SAR image matching based on epipolar geometry

Ghannadi, Mohammad Amin; Saadatseresht, M.

doi:10.1049/iet-rsn.2018.5203

Cited by 4 publications

(3 citation statements)

References 29 publications

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“…Generally, five different types of approaches can be used for multi-modal data source matching in the raster formats. These are: (1) The design and usage of feature-based matching techniques that are modified for heterogeneous data sources [25][26][27]; (2) Utilisation of the area-based matching methods by changing their approaches or similarity metrics (e.g. mutual information) [28,29]; (3) The usage of natural and manufactured objects, such as shadows [30], buildings [31] etc., that can potentially be detected or reconstructed in both heterogonous data sources; (4) Increase the radiometric similarities between the matching entities to improve the performance of traditional matching techniques [32,33]; and (5) The hierarchical and fused methods [30].…”

Section: Introductionmentioning

confidence: 99%

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Automatic refinement of ephemeris‐derived range‐Doppler model through the least‐squares matching of Sentinel‐1 Single‐Look Complex images and DEM in mountainous areas

Saeedi Amale,

Safdarinezhad

2023

IET Radar Sonar & Navi

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Range‐Doppler model is a transformation that relates ground and Single‐Look Complex SAR image spaces by knowing the instantaneous position and velocity of the sensor in its trajectory. Its instantaneous position and velocities are determined with the help of vectorial functions, which their precisions directly influence the accuracy of the range‐Doppler model. Ephemeris data is one of the sources used for the estimation of temporal functions. Some reasons can cause uncertainty in the temporal function directly derived from the satellite navigation data. Ground control points are other alternatives for calibration of the range‐Doppler model whose visual measurements are difficult in the mountainous areas of Sentinel‐1 Single‐Look Complex images due to their resolutions and distortions. The temporal functions of the range‐Doppler model are refined through numerous control points extracted from the automatic matching between Single‐Look Complex images and Digital Elevation Model. For this purpose, the radiometric and geometric similarities of the Single‐Look Complex images and Digital Elevation Model in mountainous areas are first increased based on the initial range‐Doppler model, and then their geometric discrepancies are compensated with the least‐squares image matching method. The results indicated that the proposed method in mountainous areas could automatically compensate for up to 30 pixels errors and reach sub‐pixel accuracies.

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Section: Introductionmentioning

confidence: 99%

“…The application of SAR images to produce spatial information requires the use of proper mathematical transformations that coincided with the geometry of presenting these images [1]. Regardless of generic models (e.g.…”

Section: Introductionmentioning

confidence: 99%

Automatic refinement of ephemeris‐derived range‐Doppler model through the least‐squares matching of Sentinel‐1 Single‐Look Complex images and DEM in mountainous areas

Saeedi Amale,

Safdarinezhad

2023

IET Radar Sonar & Navi

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“…GNSS-based InSAR has a series of advantages. On the one hand, the repeat-pass period of the proposed system with the Beidou Inclined GeoSynchronous Orbit (IGSO) satellite is 1 day, which is much shorter than that of the traditional InSAR system (for example, the repeat-pass periods of TerraSAR-X, Sentinel-1, COSMO-SkyMed (single satellite) and Radarsat are 11 days, 6 days, 16 days and 24 days, respectively) [7][8][9][10][11]. Thus, the system is better for some rapid deformation scenarios, such as landslides and mining collapses.…”

Section: Introductionmentioning

confidence: 99%

Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring

et al. 2021

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Global navigation satellite system (GNSS)-based synthetic aperture radar interferometry (InSAR) employs GNSS satellites as transmitters of opportunity and a fixed receiver with two channels, i.e., direct wave and echo, on the ground. The repeat-pass concept is adopted in GNSS-based InSAR to retrieve the deformation of the target area, and it has inherited advantages from the GNSS system, such as a short repeat-pass period and multi-angle retrieval. However, several interferometric phase errors, such as inter-channel and atmospheric errors, are introduced into GNSS-based InSAR, which seriously decreases the accuracy of the retrieved deformation. In this paper, a deformation retrieval algorithm is presented to assess the compensation of the interferometric phase errors in GNSS-based InSAR. Firstly, the topological phase error was eliminated based on accurate digital elevation model (DEM) information from a light detection and ranging (lidar) system. Secondly, the inter-channel phase error was compensated, using direct wave in the echo channel, i.e., a back lobe signal. Finally, by modeling the atmospheric phase, the residual atmospheric phase error was compensated for. This is the first realization of the deformation detection of urban scenes using a GNSS-based system, and the results suggest the effectiveness of the phase error compensation algorithm.

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Data Acquisition of GNSS-Based InSAR: Joint Accuracy-Efficiency Optimization of 3-D Deformation Retrieval

Wang

Liu

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In the Global Navigation Satellite System-based Synthetic Aperture Radar Interferometry (GNSS-based In-SAR) system, the 3D deformation retrieval accuracy and monitoring efficiency are very poor for the majority of the one repeat-pass period. It is necessary to select the data acquisition time and corresponding satellite combination to obtain better monitoring accuracy and efficiency. In this paper, an experimental design algorithm for GNSS-based InSAR is proposed to achieve the highest monitoring efficiency with the restriction of the 3D deformation retrieval accuracy. First, the joint optimization model is proposed, and based on an analysis of different satellite trajectories, it is proven that the optimal solution can be obtained. Second, the 3D deformation retrieval accuracy model is derived based on the bistatic configuration, and the monitoring efficiency is evaluated based on the number of effective independent points of a single SAR image. The raw data are employed to indicate the effectiveness of the proposed joint accuracy-efficiency optimization algorithm in GNSS-based InSAR.

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Efficient method for outlier removal in SAR image matching based on epipolar geometry

Cited by 4 publications

References 29 publications

Automatic refinement of ephemeris‐derived range‐Doppler model through the least‐squares matching of Sentinel‐1 Single‐Look Complex images and DEM in mountainous areas

Automatic refinement of ephemeris‐derived range‐Doppler model through the least‐squares matching of Sentinel‐1 Single‐Look Complex images and DEM in mountainous areas

Interferometric Phase Error Analysis and Compensation in GNSS-InSAR: A Case Study of Structural Monitoring

Data Acquisition of GNSS-Based InSAR: Joint Accuracy-Efficiency Optimization of 3-D Deformation Retrieval

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