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As the demand for precise navigation of aircraft increases in modern society, researching high-precision, high-autonomy navigation systems is both theoretically valuable and practically significant. Because the inertial navigation system (INS) has systematic and random errors, its output information diverges. Therefore, it is necessary to combine them with other navigation systems for real-time compensation and correction of these errors. The SAR matching positioning and navigation system uses synthetic aperture radar (SAR) image matching for platform positioning and compensates for the drift caused by errors in the inertial measurement unit (IMU). Images obtained by SAR are matched with digital landmark data, and the platform's position is calculated based on the SAR imaging geometry. However, SAR matching positioning faces challenges due to seasonal variations in SAR images, the need for typical landmarks for matching, and the lack of elevation information in two-dimensional SAR image matching. This paper proposes an airborne platform positioning method based on interferometric SAR (InSAR) interferogram matching. InSAR interferograms contain terrain elevation information, are less affected by seasonal changes, and provide higher positioning accuracy and robustness. By matching real-time InSAR-processed interferograms with simulated interferograms using a digital elevation model (DEM), three-dimensional position information about the matching points has been obtained. Subsequently, a three-dimensional positioning model for the platform has bene established using the unit line-of-sight vector decomposition method. In actual flight experiments using an FMCW Ku-band Interferometric SAR system, the proposed platform positioning framework demonstrated its ability to achieve precise positioning in the absence of signals from the global navigation satellite system (GNSS). [ABSTRACT FROM AUTHOR]

To explore the degree of constraint by Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) data on the Maduo earthquake within a layered earth model structure and to gain an insight into the seismogenic mechanism and the seismic risk in the surrounding area, this study employs D-InSAR technology to acquire the InSAR co-seismic deformation field of the Maduo earthquake on 22 May 2021. Utilizing both GNSS and InSAR data, the inversions constrained by single and joint data are conducted and compared to determine the co-seismic slip model and fault plane stress distribution of the Maduo earthquake. Additionally, this paper calculates the Coulomb stress changes induced by 14 M ≥ 7 strong earthquakes, considering co-seismic effects, post-seismic viscoelastic relaxation, and inter-seismic tectonic stress loading, on 19 fault segments within the Bayan Har block research area (96°E~106°E, 29°N~36°N) since 1900. The findings are as follows: (1) The maximum line-of-sight (LOS) deformation was approximately 0.9 m. The joint inversion rupture was primarily located in the Dongcao Along Lake section (~98.6°E), aligning with previous research outcomes. (2) The cumulative Coulomb stress at the Maduo earthquake's source location was −0.1333 MPa, while the inter-seismic stress loading amounted to 0.0745 MPa. The East Kunlun Fault, Maduo–Gande Fault, Ganzi–Yushu Fault, and Dari Fault C exhibited considerable stress loading, warranting attention due to heightened seismic risk. (3) Based on three different co-seismic slip models, the stress disturbance results caused by the Maduo earthquake to the surrounding area and fault did not differ significantly. After the earthquake, the seismogenic fault still has high seismic risk. [ABSTRACT FROM AUTHOR]

Landslides along the Three Gorges Reservoir in China pose a threat to coastal residents and waterway safety. To reduce false positive misjudgments caused by a sudden local change in the landslide deformation curve, in this paper, we propose an effective method for predicting the deformation trend of reservoir bank landslides. We take reservoir bank landslides in the Wanzhou District of the Three Gorges Reservoir area as the research object. The Time-Series Interferometric Synthetic Aperture Radar (InSAR) method and 62 Sentinel-1A images from 2018 to 2022 were selected for landslide deformation monitoring, and the Hurst index was calculated to characterize the deformation trend. Furthermore, we propose a method for predicting the deformation trend based on the statistical distribution of deformation rates and the physical significance of the Hurst index. After the field survey and Global Positioning System (GPS) verification, the Time-Series InSAR results are shown to be reliable. We take the Sifangbei landslide as a representative case to analyze the validation results. It is found that the determined Sifangbei landslide deformation trend is consistent with the conclusions for the region. In addition, the deformation trend of a reservoir bank slope has obvious spatial and temporal differences. Changes in the reservoir water level and concentrated rainfall play roles similar to those of catalysts. The proposed method, involving the combination of Time-Series InSAR and the Hurst index, can effectively monitor deformation and predict the stability trend of reservoir bank landslides. The presented research results provide new ideas and solutions for landslide prevention and risk mitigation in reservoir areas. [ABSTRACT FROM AUTHOR]

With the rapid development of interferometric synthetic aperture radar (InSAR) measurement technology, its measurement accuracy requirements are increasing. Atmospheric delay errors must be corrected, especially in the case of crustal deformation monitoring, the 20% variation of tropospheric water vapor among InSAR pairs generally produces range from 10 cm to 14 cm deformation errors. Such errors can be of the same magnitude as the annual changes in crustal deformation, or even greater, masking crustal deformation information and seriously affecting the results of crustal deformation monitoring. Therefore, in order to obtain a more accurate InSAR atmospheric delay correction model, this paper calculated and integrated atmospheric delays that were estimated by different sources, including the 37 pressure levels of the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF)) numerical weather prediction model, ECMWF Reanalysis v5 (ERA5), and Global Navigation Satellite System (GNSS) measurement data from the crustal movement observation network of China, based on the variance component estimation (VCE) weighting method. The results showed that the integrated model, based on the VCE method, is better than the generic atmospheric correction online service (GACOS) model for InSAR measuring of crustal deformation. The precision in monitoring crustal deformations was improved by approximately 5 mm, the correlation coefficient of atmospheric delay errors and crustal deformations improved from 0.287 to 0.347, and accuracy improved by approximately 25%. However, the improvement in accuracy was limited because of system error decoherence that was induced by atmospheric noise caused by abundant vegetation or snow cover. Therefore, in order to achieve more accurate results, we recommend the adoption of the multi-source integrated atmospheric delay correction model, based on the VCE method, for InSAR high-precision measuring of crustal deformation and seismic activities. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) enables us to obtain precipitable water vapor (PWV) maps with high spatial resolution through the phase difference caused by refraction in the atmosphere. Although previous studies have evaluated the error level of InSARPWV observations, they validated it only with C-band InSARPWV observations. Since ionospheric disturbance seriously contaminates the InSAR phase in the case of the lower-frequency SAR system, it is necessary for a PWV error level evaluation correcting the ionospheric effect appropriately if we use lower-frequency SAR systems, such as the Advanced Land Observing Satellite-2 (ALOS-2). In this paper, we evaluated the error level of the L-band InSARPWV observation obtained from ALOS-2 data covering four areas in Japan. We compared the InSAR observations with global navigation satellite system (GNSS) atmospheric observations and estimated the L-band InSARPWV error value by utilizing the error propagation theory. As a result, the L-band InSARPWV absolute error reached 2.83 mm, which was comparable to traditional PWV observations. Moreover, we investigated the impacts of the seasonality, the interferometric coherence, and the height dependence on the PWV observation accuracy in InSAR. [ABSTRACT FROM AUTHOR]

Excessive exploitation of the groundwater has resulted in obvious three-dimensional (3D) deformation features on the surface of the Beijing Plain. This paper, by combining Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) technologies, has obtained time-series information of the 3D surface deformation in the Beijing Plain, analyzing its spatial distribution characteristics. On this basis, the relationship between different controlling factors with the 3D deformation of the surface has been analyzed as well. The following results are obtained: (1) From 2013 to 2018, the land subsidence, which generally showed the trend of slowing down, was mainly concentrated in the eastern, northern, and southern regions of Beijing Plain, with multiple subsidence centers. (2) Under the International Terrestrial Reference Frame 2005 (ITRF2005), the horizontal direction of all GPS points in the plain is basically the same, with the dominant movement direction being NE112.5°~NE113.8°. Under the Eurasian reference frame, the horizontal movement rate of GPS points significantly decreases. The movement rate and direction of each point are not characteristic of overall trend activity. (3) The distribution and extent of the 3D surface deformation in the Beijing Plain are controlled by the basement structure. Part of the subsided area corresponds to a Quaternary depression formed at the junction of active faults disrupting the area. Similarly, the distribution of horizontal deformation in the E-W and N-S directions of the plain is controlled by the regional basement structure comprising major faults bounding horizontal deformation. (4) Groundwater exploitation is the main cause of the 3D surface deformation in the Beijing Plain. The groundwater funnels of the second and third confined aquifer are in suitable agreement with the land subsidence. The horizontal movement in the Beijing Plain is either directed toward the center of the groundwater or the land subsidence funnel, and the deformation is directed from areas with higher to areas with lower groundwater levels. [ABSTRACT FROM AUTHOR]