Interferometry Technology Research Articles

SAR interferometry on full scatterers: Mapping ground deformation with ultra-high density from space

Spaceborne time series SAR interferometry (TS-InSAR) technology has been widely applied in ground deformation monitoring. The current popular TS-InSAR are carried out mainly on permanent scatterers (PS) or distributed scaterrers (DS), which can map the ground deformation on sparse targets with high or moderate coherence. However, high-precision and high-density deformation monitoring is always restricted by atmospheric artifacts and surface decorrelation, especially over nonurban areas. Here we show that the ground deformation can be precisely mapped with high density by spaceborne InSAR technique. We proposed a full scatterers InSAR (FS-InSAR) methodology, which can significantly improve the quality of the interferograms by applying a dual-scale temporal low-pass filter (DTLF) to separate both atmospheric and noisy phases from deformation phases, without external atmospheric data. Simulation experiments were conducted to determine the small-scale and large-scale window sizes and evaluate the effectiveness of DTLF. Then we applied the FS-InSAR method to the Tianjin-Tangshan region, China using Sentinel-1 data, assessed the regenerated differential low-frequency phases, and validated the results with leveling measurements and groundwater depth data. What's more, detailed ground deformation was retrieved over the Tangshan mining area with an unprecedented density of 98.55%. Our results demonstrate that the FS-InSAR strategy contrasts sharply with the previous PS-InSAR or DS-InSAR methods by simultaneously solving the two bottleneck problems of atmospheric artifacts and decorrelation in most cases except for water bodies or dense vegetations such as rainforest, thereby it is of great importance for future monitoring and understanding the ground deformation to prevent and control geological disasters.

Application of multi-source remote sensing technology in UAV communication control system

Abstract Unmanned aerial vehicles (UAVs) are crucial in various sectors but face challenges in communication reliability. This paper introduces a cutting-edge UAV communication control system, designed using time-series synthetic aperture radar interferometry (InSAR) technology and support vector machine (SVM) classification. Our findings reveal exceptional communication link performance across multiple flight scenarios, notably achieving a bit error rate (BER) of 0.001% in cruising mode. Additionally, the system demonstrated remarkable reception sensitivity, closely aligning with theoretical predictions at −81.1 dBm. This innovative approach utilizes multi-source remote sensing to significantly enhance UAV communication, offering a novel strategy for addressing UAV communication dilemmas.

SURFACE DEFORMATION MONITORING IN SHIYAN BASED ON MULTI-TEMPORAL INSAR TECHNOLOGY

Abstract. In recent years, InSAR technology has continuously developed and become a mainstream technology for monitoring wide-area surface deformation. In this study, Shiyan was selected as the work area, and Multi-temporal Synthetic Aperture Radar Interferometry (MT-InSAR) technology was used to monitor surface deformation over a long time series. The temporal and spatial distribution characteristics of the InSAR monitoring results were analyzed. The surveillance results showed that from January 2021 to March 2023, Shiyan experienced noticeable uneven settlement, with a deformation rate range of [−111.8mm/a, 20.9mm/a]. The maximum cumulative deformation variable reached −212.9mm, and more than 70 deformation zones were identified during the study period. The main causes of deformation were also analyzed. This study provides a reference for large-scale surface deformation monitoring and disaster management in Shiyan.

A new snow depth retrieval method by improved hybrid DEM differencing and coherence amplitude algorithm for PolInSAR

Snow depth is a critical parameter for measuring the variations of the snowpack, and its measurement also influences the accuracy of hydrological and climate models. Polarimetric SAR interferometry (PolInSAR) technology combines the capabilities of Polarimetric SAR (PolSAR) and Interferometric SAR (InSAR), and has significant potential for retrieving snow depth. The hybrid DEM differencing and coherence amplitude algorithm (HDCA) is a robust algorithm for PolInSAR data, but encounters such problems as uncertainty in finding the ground scattering phase center, impure volume decorrelation, and the lack of consideration of the dense medium characteristic of snow. In this study, the HDCA is improved by optimizing the phase and decorrelation parameters and by considering the dense medium characteristic of snow. First, the Freeman-Duren decomposition method is put forward to extract the ground and volume scattering phase centers from the snow. Second, the coherence region boundary estimation method is proposed to optimize the volume decorrelation. Following this, the parameter assumed by the original method in free space is adjusted by considering the dense medium characteristic of snow. Finally, the Ku band UAV SAR data were applied to validate the new method, and in-situ data were used to assess its accuracy. The correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) of the proposed method are 0.93, 3.59 cm, and 2.98 cm, respectively, and were significantly superior to those of the original HDCA method of 0.74, 7.44 cm, and 6.04 cm, respectively.

Application of gravitational wave detection technology in astronomical observations

Gravitational waves are waves that propagate through space and time due to the interaction of gravity, representing a completely new physical phenomenon. This article reviews the background and issues of gravitational wave detection, with a focus on the progress of interdisciplinary research. It was not until 2015 that researchers successfully detected gravitational waves for the first time, capturing gravitational wave signals from the merger of two black holes using laser interferometry technology. This breakthrough confirms the predictions of Einstein's general relativity and opens a new chapter in the study of gravitational waves. Gravitational wave detection technology not only provides a new way to observe the universe, but also provides clues for studying the mysteries of the universe such as black holes, dark matter, and dark energy. Gravity wave detection technology also has potential communication application prospects, such as quantum gravity communication and long-distance communication, which brings new possibilities for future communication technology. In the future, there expects to be more success of gravitational wave detection and the continuous contribution of gravitational wave research in unlocking the mysteries of the universe and advancing the forefront of science.

Radar Interferometry for Urban Infrastructure Stability Monitoring: From Techniques to Applications

Urban infrastructure is an important part of supporting the daily operation of a city. The stability of infrastructure is subject to various deformations related to disasters, engineering activities, and loadings. Regular monitoring of such deformations is critical to identify potential risks to infrastructure and take timely remedial actions. Among the advanced geodetic technologies available, radar interferometry has been widely used for infrastructure stability monitoring due to its extensive coverage, high spatial resolution, and accurate deformation measurements. Specifically, spaceborne InSAR and ground-based radar interferometry have become increasingly utilized in this field. This paper presents a comprehensive review of both technologies for monitoring urban infrastructures. The review begins by introducing the principles and their technical development. Then, a bibliometric analysis and the major advancements and applications of urban infrastructure monitoring are introduced. Finally, the paper identifies several challenges associated with those two radar interferometry technologies for monitoring urban infrastructure. These challenges include the inconsistent in the distribution of selected measurements from different methods, obstacles arising from rapid urbanization and geometric distortion, specialized monitoring techniques for distinct urban features, long-term deformation monitoring, and accurate interpretation of deformation. It is important to carry out further research to tackle these challenges effectively.

Efficient Hapten-Specific Biopanning Strategy Based on the Fe3O4@ENR-Functionalized Core-Shell Magnetic Nanoparticles.

The biopanning of target-specific phages is one of the most critical steps in the preparation of single-domain antibodies. In the traditional biopanning of haptens, the nonspecific binding of library phages to macromolecular proteins is one of the most challenging problems in preparing single-domain antibodies. In this research, Fe3O4@ENR-functionalized core-shell magnetic nanoparticles (FMNPs) were silylated and aminated by tetraethyl orthosilicate and (3-aminopropyl)triethoxysilane, and target enrofloxacin was coupled onto the surface by the carbodiimide method. The magnetic nanoparticles were characterized by Fourier transform infrared spectroscopy, particle size distribution, zeta potential, transmission electron microscopy observation, and indirect enzyme-linked immunosorbent assay (ELISA). A biopanning strategy based on Fe3O4@ENR FMNPs was then established to solve the problem in the traditional solid-phase biopanning process. The results showed that a considerable number of enrofloxacin (ENR)-positive phages were screened by only one round of biopanning. Finally, two ENR-specific shark-derived single-domain genes were identified and validated by monoclonal phage ELISA, gene sequencing, and biolayer interferometry technology. Our study provides a new biopanning strategy based on Fe3O4@ENR FMNPs for efficiently providing phages specific to haptens.

Five-Step Phase-Shift-Based Multiwavelength Averaging for Extrinsic Fabry–Perot Interferometric Sensors

In order to address issues such as low demodulation accuracy, large demodulation errors, small dynamic range, and complex algorithms for the extrinsic Fabry–Perot interferometric (EFPI) sensor, a five-step phase-shift algorithm based on a multiwavelength (MW)-averaging method is proposed to improve demodulation speed, noise stability, dynamic range, and noise suppression. The proposed demodulation method utilizes white-light interferometry (WLI) technology to acquire the reflection spectra and extract the five-step phase-shift signals at Ns consecutive operating points. The demodulation results of Ns sets of five-step phase-shift signals are averaged to obtain the average demodulated phase and cavity length variation. Theoretical analysis demonstrates the significant effects of the MW demodulation method on demodulation parameter errors and noise suppression. Particularly, when the demodulation parameter θ = π/2 rad, the method exhibits excellent stability against demodulation parameter error-induced instability. Moreover, it greatly improves noise suppression and reduces noise fluctuations. Numerical simulations are conducted to validate the performance of the proposed demodulation method. Compared with the traditional single-wavelength (SW) five-step phase-shifting demodulation method, the MW demodulation method exhibits stronger noise- and harmonic-suppression capabilities as the number of averaging wavelengths Ns increases. The harmonic distortion of the MW demodulation method with Ns = 128 is 20 dB lower than that of the SW demodulation method, and the noise is 15 dB lower. Furthermore, the proposed method effectively suppresses the influence of demodulation parameter errors on signal demodulation. This proposed demodulation method has the potential for fast real-time dynamic demodulation. It has great significance and application in the field of weak signal detection in fiber-optic sensors with interferometer structures and has enormous advantages in noise-suppression in complex environments.

AdpPL: An adaptive phase linking-based distributed scatterer interferometry with emphasis on interferometric pair selection optimization and adaptive regularization

The distributed scatterer (DS) interferometry (DSI) technology is a powerful geodetic tool for measuring the deformation over abundant land covers. As a state-of-the-art DSI technology, the SqueeSAR approach considered the statistical behavior of the decorrelated DS and proposed the phase triangulation algorithm (PTA) as the pioneering implementation of the phase linking (PL) theory to estimate the equivalent single-reference (ESR) phases from all interferometric combinations. Subsequently, many advanced estimators of the systematic phase series have been introduced. Interestingly, this paper has demonstrated that the utilization of weakly coherent interferometric pairs is not conducive to the theoretical accuracy improvement of the PL theory in case of the fast decorrelation scenario. Moreover, the reduction of the small baseline scales will worsen the positive definite degree of the time series coherence matrix, which makes the ill-posed solution problem more serious. Therefore, this paper proposes a novel adaptive PL (AdpPL) method integrating the following two innovations for mapping surface deformation: 1) in terms of the interferometric pair selection optimization (IPSO), this paper performs the homogeneity measure-based IPSO (HoMeIPSO) method to remove the lowly coherent candidate subset progressively and select the moderate interferometric pairs adaptively; 2) in terms of the robust parameter estimation, an adaptive regularization (AdpReg) approach suggests selecting an optimal damping factor according to the minimum fitting error of all interferogram observables. Experimental results demonstrate that the proposed method can restore the systematic phase series more clearly and detect the deformation area with spatially highly dynamic characteristics successfully.

Biolayer Interferometry Technology to Detect Interactions between Ligand and Analyte

Biolayer Interferometry Technology to Detect Interactions between Ligand and Analyte

Structural Insights into the Binding of Red Fluorescent Protein mCherry-Specific Nanobodies.

Red fluorescent proteins (RFPs) have broad applications in life science research, and the manipulation of RFPs using nanobodies can expand their potential uses. However, the structural information available for nanobodies that bind with RFPs is still insufficient. In this study, we cloned, expressed, purified, and crystallized complexes formed by mCherry with LaM1, LaM3, and LaM8. Then, we analyzed the biochemical properties of the complexes using mass spectrometry (MS), fluorescence-detected size exclusion chromatography (FSEC), isothermal titration calorimetry (ITC), and bio-layer interferometry (BLI) technology. We determined the crystal structure of mCherry-LaM1, mCherry-LaM3, and mCherry-LaM8, with resolutions of 2.05 Å, 3.29 Å, and 1.31 Å, respectively. In this study, we systematically compared various parameters of several LaM series nanobodies, including LaM1, LaM3, and LaM8, with previously reported data on LaM2, LaM4, and LaM6, specifically examining their structural information. After designing multivalent tandem LaM1-LaM8 and LaM8-LaM4 nanobodies based on structural information, we characterized their properties, revealing their higher affinity and specificity to mCherry. Our research provides novel structural insights that could aid in understanding nanobodies targeting a specific target protein. This could provide a starting point for developing enhanced mCherry manipulation tools.

Parallel unambiguous generalized phase-shifting and T-spline fitting algorithms for optical micro-structured surface 3D topography metrology.

3D topography metrology of optical micro-structured surfaces is critical for controlled manufacturing and evaluation of optical properties. Coherence scanning interferometry technology has significant advantages for measuring optical micro-structured surfaces. However, the current research faces difficulties of designing high accuracy and efficient phase shifting, and characterization algorithms for optical micro-structured surface 3D topography metrology. In this paper, parallel unambiguous generalized phase-shifting and T-spline fitting algorithms are proposed. To avoid phase ambiguity and improve the accuracy of the phase-shifting algorithm, the zero-order fringe is determined by the iterative envelope fitting with Newton's method, and the accurate zero optical path difference is determined by a generalized phase-shifting algorithm. In particular, the calculation procedures of the multithreading iterative envelope fitting with Newton's method and generalized phase shifting are optimized with the graphics processing unit-Compute Unified Device Architecture kernel function. Additionally, to fit the base form of optical micro-structured surfaces and characterize the surface texture and roughness, an effective T-spline fitting algorithm is proposed by optimizing the preimage of the T-mesh with image quadtree decomposition. Experimental results show that the surface reconstruction of optical micro-structured surfaces using the proposed algorithm is more accurate, and the efficiency is 10 times higher than that of current algorithms; the time of the surface reconstruction is less than 1s. Compared with the current B-spline method, the accuracy of roughness characterization using the proposed T-spline algorithm is improved by more than 10%.

Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS−InSAR

Potential landslides in the mountainous areas of southwest China pose a serious threat to the lives and property of local residents. Synthetic aperture radar interferometry (InSAR) technology has the advantages of wide coverage, all weather applicability, and low cost and can quickly and accurately identify large range of active landslides, making it a useful geodetic tool for the early identification and prevention of landslides. This paper employed small baseline subset InSAR (SBAS−InSAR) technology and ascending and descending Sentinel−1 data from January 2019 to December 2021 to early identify active landslides in the Maoxian County to Li County National Highway (G317 and G213). The InSAR deformation results were verified by geometric distortion analysis, optical remote sensing interpretation, and field investigation, and 115 active landslides were successfully determined, among which 23 active landslides were identified by ascending and descending Sentinel−1 data together. In addition, InSAR deformation results show that fault, stratigraphic lithology, and rainfall are the three main factors that accelerate the deformation of active landslides and can trigger new active landslides. This study can provide an important reference for the early identification and prevention of landslides in mountainous areas.

Spatiotemporal Characteristics of the Mud Receiving Area Were Retrieved by InSAR and Interpolation

The mud receiving area is an important sand storage area for dredging sea sand reclamation and sand-dumping in the waterway. The sediment accumulation area generated in the process of sand dumping and sand storage has an impact on the surrounding transportation facilities and the normal use of the entire sand storage area. From 6 August 2021 to 9 May 2022, The Sentinel-1A 24-view SLC data covering the sludge area were used to monitor the safety around the seawall road by InSAR technology. Synthetic aperture radar differential interferometry (Differential InSAR, D-InSAR) technology can obtain surface micro deformation information through single-time differential interference processing, mainly used for sudden surface deformation. D-InSAR technology detected five accumulation areas with a thickness of more than 10 cm near the seawall road, earth embankment, and cofferdam, and TS-InSAR (Time series InSAR) technology was used to retrieve the deformation of the surrounding road. The road settlement is a slight settlement distributed between ±5 mm/a. This paper uses the leveling results combined with variance analysis to verify the fusion of different TS-InSAR methods while considering the area of data loss due to causes such as loss of coherence. This paper also considers the common ground continuity and uses the adjacent interpolation and bilinear interpolation algorithm to improve knowledge of the study area seawall road and the surrounding soil embankment deformation data of the road. Compared with the leveling data, the difference between the missing data and the leveling data after interpolation is stable at about 1–7 mm, which increases the risk level of part of the road which needs to be maintained. It provides a reference method to make up for the missing data caused by ground incoherence.

Smooth Surface Defect Detection of Metal Workpiece Based on Digital Speckle Pattern Interferometry

When the existing defect detection methods are used to detect the defects on the smooth surface of metal workpieces, there is a big difference between the detection results and the actual results, and the detection accuracy is low. Therefore, the digital speckle pattern interferometry (DSPI) technology is introduced in this paper to study the design of the detection method of smooth surface defects of the metal workpieces. In this paper, the smooth surface of metal workpiece is measured by using digital speckle interferometry. The speckle on the measurement image is processed by the Laplace algorithm, and the speckled area is automatically extracted; The defects on the smooth surface of the metal workpiece are detected and located according to the speckled area. The comparative experiments show that the detection errors of the two new detection methods are less than 0.1 µm in practical application, and the detection accuracy is high, which can realize the high-precision detection of smooth surface defects of metal workpieces.

Displacement measurement of sub-nanometer resolution using space-domain active fiber cavity ring-down technology

A displacement sensor of sub-nanometer resolution using space-domain active fiber cavity ring-down (FCRD) technology was developed. In our scheme, by combining active FCRD with frequency-shifted interferometry technology, a sensitivity of 0.05 km−1 ·nm−1 was achieved and the stability was improved mostly because this scheme is free from thepowerfluctuationofalight source, benefited to the use of low-noise Bi-EDFA and the differential detection method to reduce the direct current noise. Besides the first sensitivity amplification process is involved in this technique due to the multiple times rounds of interaction between the light pulse and the sensor head in the fiber cavity, the secondary sensitivity amplification process is realized by using a Bi-EDFA to compensate the inherent cavity loss of fiber cavity, which results in a significantly improvement in resolution. The experimental results show that our proposed displacement sensor can achieve a resolution of up to 0.3 nm with stability of 1.3 %.

Land Subsidence Evolution and Simulation in the Western Coastal Area of Bohai Bay, China

Groundwater overexploitation and loading of buildings have been the main factors triggering land subsidence along the west coast of Bohai Bay, China, since the 2000s. Uneven subsidence has been causing damage to buildings and civil facilities, loss of elevation, increasing the risk of flood and seawater intrusion, and threatening the safety of people’s lives and property. This paper analyzed the spatial and temporal features of land subsidence along the coastal area from 2003 to 2010 and from 2015 to 2020, respectively. The relations between the initiating factors and land subsidence were explored. Then, the simulation model of land subsidence was constructed through a deep learning method. During the process, multiple data were collected, including land satellite (Landsat), environmental satellite advanced synthetic aperture radar (ENVISAT ASAR) and Sentinel-1 images, leveling data, lithological data, and groundwater level data. The area occupied by buildings and vertical displacement were extracted by using supervised classification, small baseline subset (SBAS), and persistent scatterer interferometry (PSI) technologies. The gated recurrent unit (GRU) neural network was adopted to simulate the evolution of land subsidence. Results showed that the maximum annual vertical displacement rate decreased from −94 mm/yr during 2003–2010 to −87 mm/yr during 2015–2020. The correlation efficiency between the groundwater level of the third confined aquifer group and land subsidence was larger than the area occupied by buildings and the compressible layer thickness with subsidence. The constructed GRU neural network model can simulate subsidence from September 2019 to December 2019, with the overall RMSE and MAE being 3.16 mm and 2.19 mm, respectively. This work can facilitate an understanding of the evolution and prevention of land subsidence along the west coast of Bohai Bay, which will provide information for policy decisions and flood-fighting plans of the worldwide coastal cities.

Mechanism investigation of Caspase-8/GSDMC dependent immunogenic cell death induced by Ophiopogonin B in NSCLC cells

Ophiopogonin B (OP-B) as a bioactive component of Radix Ophiopogon Japonicus has been reported to induce various kinds of cell death of non-small cell lung cancer (NSCLC) cells, while the underline mechanism is unknown. Herein, through affinity chromatography, Biolayer Interferometry (BLI), and molecular docking simulation technology, we verified HSP90-α to be the potential target of OP-B in A549 cells. Further investigation indicated that HSP90-α promoted translocation of STAT3 to the nuclear and further promoted the expression of GSDMC, which enhanced its competitive binding to Caspase-8, and at last resulted in pyroptosis of the cell. In addition, investigation in A549 orthotopic tumor nude and NCG mice model verified that OP-B-induced pyroptosis of cancer cells leaded to recruitment of NK cells to lung cancer tissue. Taken together, through targeting at HSP90-α, OP-B induced Caspase-8/GSDMC dependent pyroptosis and further resulted in ICD of A549 cells in vitro and in vivo.

Detecting seasonal and trend components in PS-InSAR displacement time series

Persistent scatterers synthetic aperture radar interferometry (PS-InSAR) technology has been applied in the context of deformation monitoring of transportation infrastructures such as bridges, highways, and railways. However, extracting and interpreting information from long-time series displacement obtained using PS-InSAR is a complex and demanding task. In this study, time series analysis was used to post-process the displacement time series derived from PS-InSAR using 100 stripmap mode images collected by TerraSAR-X satellite during 13 April 2010 and 13 December 2019. Seasonal and trend decomposition using loess (STL) and variational modal decomposition (VMD) were combined to estimate the different periodic and trend components of the total displacement time series. Temperature correlation was then generated by associating the different period components with the temperature change. The results show that the deformation of Sihui overpass, Sifang overpass and Shibalidian overpass in Beijing Fourth Ring Road highway is obvious. The trend components obtained by STL decomposition of the selected typical points are primarily nonlinear deformation, and the deformation of Sifang overpass, Shibalidian overpass and Liuxiang overpass slows to varying degrees. After decomposing the displacement time series into several intrinsic mode functions (imf) with finite bandwidth using VMD, the thermal expansion phenomenon is pronounced on the main bridge and approach bridge of some overpasses. Seasonal imf1 is an annual periodic that appears to be highly positively correlated with temperature change. Seasonal imf2 is a period term of greater than one year that confirms that the bridges exhibit other periodic seasonal components in addition to the seasonal deformation of annual period. The thermal expansion characteristics of different periodic seasonal components that are explored in this study can provide valuable information for better understanding the thermal expansion evolution process, and these findings are important scientific significance for bridge structure health monitoring.

Source Model for the 2022 Qinghai Menyuan Ms 6.9 Earthquake Based on D-InSAR

On 8 January 2022, an Ms 6.9 earthquake occurred in Menyuan County, Qinghai Province, China. This earthquake ruptured a patch of the Qilian-Haiyuan fault in the northeast margin of the Qinghai-Tibet Plateau. In order to understand the seismogenic structure of this earthquake and analyze the fault activity, we use differential synthetic aperture radar interferometry (D-InSAR) technology to obtain a complete co-seismic displacement field on the surface, and use pixel tracking algorithm to extract the trace of the ruptured fault. The slip distribution of the seismogenic fault was inverted using the steepest descent method, and the Coulomb stress change caused by the earthquake was also calculated. Surface deformation results show that the Menyuan earthquake produced obvious surface displacements in an area of 50 × 40 km2. The displacements are mainly distributed in the western segment of the Lenglongling fault and the eastern segment of the Tolaishan fault. The maximum displacements in the ascending and descending orbits in the LOS direction are 59.7 and 94.7 cm, respectively. The co-seismic slip results show that the strike, dip and average slip angles of the seismogenic fault are 108°, 79° dipping to SW, and 4°, respectively. On the whole, the fault is mainly of left-lateral, with a small amount of thrust component and only one co-seismic rupture center in our inversion result. The rupture center is located at a depth of ∼5 km below the surface, and the maximum slip is 3.1 m. The total seismic moment released by this earthquake is 1.28 × 1019 N·m, and the corresponding moment magnitude is 6.67. Finally, the static Coulomb stress change results show that parts of the Lenglongling fault, the Tolaishan fault, the Sunan-Qilian fault and the Minyue-Damaging fault are loaded, emphasizing the importance for earthquake risk assessment of these fault.