A system and method for monitoring subsidence of artificial islands at sea

Abstract

The present invention discloses a subsidence monitoring system and method for an artificial island at sea, which relates to the field of artificial island subsidence measurement technology, and includes a monitoring and management center, wherein the monitoring and management center is communicatively connected with a GNSS PPP module, a leveling module, an InSAR monitoring module, a data processing module, a data fusion analysis module, and a deformation result module, wherein the modules are electrically connected; the GNSS PPP module uses a GNSS receiver to collect carrier phase and code pseudorange data. The present invention realizes full coverage subsidence monitoring from point to line to surface by integrating GNSS PPP, leveling, and InSAR technologies, overcomes the limitations of a single monitoring technology, improves the comprehensiveness, continuity, and high precision of monitoring, and the system can timely detect and warn of the subsidence risk of the artificial island.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial island settlement measurement, and in particular to a system and method for monitoring offshore artificial island settlement. Background Art

[0002] In the prior art, the commonly used monitoring methods for the settlement of artificial islands mainly include conventional leveling, bedrock mark and layered mark measurement, GNSS monitoring, distributed fiber optic sensing technology and airborne LiDAR, etc., and the existing single monitoring technical means have certain limitations to a greater or lesser extent, either single point deformation, unable to reflect the settlement state of the artificial island as a whole; even if the LiDAR technology can achieve surface monitoring, it is also restricted by weather or low efficiency of large-scale monitoring; and the InSAR technology can make up for the shortcomings and defects of these existing technical means, but there is also a need for external data verification of the monitoring results. In addition, the overall settlement monitoring of the artificial island requires a starting benchmark, and GNSS PPP can just solve this problem. In addition, the monitoring points connected by the leveling measurement can be mutually verified with the InSAR monitoring results. Therefore, the present invention proposes to integrate GNSS PPP, leveling and InSAR technology to form a full-coverage settlement monitoring method from point to line to surface for different needs of artificial islands. Summary of the invention

[0003] The present invention aims to provide a system and method for monitoring the subsidence of an offshore artificial island, so as to solve the problems raised in the above-mentioned background technology.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] In a first aspect, an offshore artificial island settlement monitoring system includes a monitoring management center, wherein the monitoring management center is communicatively connected to a GNSS PPP module, a leveling module, an InSAR monitoring module, a data processing module, a data fusion analysis module, and a deformation result module, wherein electrical signals are connected between the modules;

[0006] The GNSS PPP module uses the GNSS receiver to collect carrier phase and code pseudorange data, combines high-precision satellite orbit and clock error data, and uses a model correction method to reduce errors to achieve high-precision positioning and provide a high-precision spatial positioning benchmark as a starting benchmark for leveling and InSAR monitoring.

[0007] The leveling module adopts a round-trip measurement method to evenly distribute monitoring points to form a closed-loop measurement route, and performs data verification and adjustment calculation to obtain deformation results, providing deformation data in the vertical direction of the artificial island surface, which is mutually verified with GNSS PPP and InSAR monitoring results to improve the comprehensiveness and accuracy of monitoring;

[0008] The InSAR monitoring module uses InSAR technology to observe the same target object using radars at different spatial positions, obtain SAR images and perform interference processing to obtain deformation information of the target, thereby realizing large-scale, continuous and high-precision deformation monitoring of the surface of the artificial island, and can capture tiny surface deformations, providing important data support for overall stability assessment;

[0009] The data processing module, based on the time series InSAR technology of the SBAS method, estimates and weakens the atmospheric phase error and terrain error through the least square method and singular value decomposition algorithm, improves the deformation signal-to-noise ratio, and improves the deformation monitoring accuracy;

[0010] The data fusion analysis module is used to fuse the data of GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points, unify them into the same coordinate frame, compare and verify them with each other, and obtain comprehensive deformation results. By fusing multi-source data, the accuracy and reliability of monitoring results are improved, the stability of the artificial island is fully reflected, and potential safety hazards are discovered in a timely manner.

[0011] The deformation result module is used to analyze and process the comprehensive deformation results obtained by the data fusion analysis module, obtain the deformation rate diagram of the entire artificial island, provide the time series deformation results of any feature point during the monitoring period, provide detailed deformation data for decision makers, and help evaluate the stability of the artificial island.

[0012] A further improvement of the technical solution of the present invention is that in the GNSS PPP module, the process of acquiring the spatial positioning reference is:

[0013] The GNSS receiver simultaneously receives carrier phase and code pseudorange observations from multiple satellites, and uses the IGS to obtain high-precision satellite orbit and clock error data to reduce satellite orbit and clock error errors.

[0014] Based on carrier phase and code pseudorange observations, combined with high-precision satellite orbit and clock error data, the GNSSPPP observation equation is constructed;

[0015] The model correction method is applied to reduce the influence of various error sources on the positioning results, including the total tropospheric delay effect, ionospheric delay correction, receiver and satellite clock error correction, and tidal correction. Among them, the tropospheric delay correction uses the tropospheric delay model to estimate and correct the delay caused by the signal passing through the atmosphere. The ionospheric delay correction uses a dual-frequency signal to reduce the influence of the ionosphere on the signal. The receiver and satellite clock error correction uses high-precision satellite clock error data to correct the time difference between the receiver and the satellite. The tidal correction corrects the deformation caused by the earth's tide, including the solid tide and the ocean tide load effect. The expression for calculating the total tropospheric delay effect is:

[0016] ;

[0017] in, is the total tropospheric delay on the propagation path; the component of the total tropospheric delay in the zenith direction is , ; , Mapping functions corresponding to dry and wet delays, such as NMF function, VMF function, etc.

[0018] The dual-frequency ionosphere-free linear combination model is used to reflect the geometric relationship between the observed quantity and the unknown parameters, and precise single-point positioning is performed. The combined observation values ​​are analyzed to eliminate the influence of the ionosphere on the positioning accuracy.

[0019] Using the corrected data, the three-dimensional coordinates of the receiver are calculated through the precise point positioning algorithm, and the calculated three-dimensional coordinates are verified to evaluate the positioning accuracy to ensure that the monitoring requirements are met;

[0020] The calculated high-precision three-dimensional coordinates are used as the starting reference points for leveling and InSAR monitoring, providing a reference for other monitoring modules.

[0021] A further improvement of the technical solution of the present invention is that the expression of the GNSS PPP observation equation is:

[0022] ;

[0023] ;

[0024] in, , represent the station and satellite respectively, is the speed of light, is the star station distance; , are the code pseudorange and phase pseudorange observation values ​​respectively, is the carrier phase observation value, is the receiver clock error, is the satellite clock error, , are the tropospheric and ionospheric delay corrections, is the carrier phase ambiguity, , is the corresponding observation noise;

[0025] The expression of the precise point positioning is:

[0026] ;

[0027] ;

[0028] in, , are the phase and code pseudorange combined observation values, is the frequency, , They are and The frequency of the carrier phase observations; , Respectively , Frequency raw pseudorange observations; , Respectively , Frequency phase observations.

[0029] A further improvement of the technical solution of the present invention is that in the leveling measurement module, the process of obtaining the deformation result is:

[0030] According to the topography, geological conditions and monitoring requirements of the artificial island, the monitoring points should be evenly distributed to form a closed-loop measurement line. The monitoring points should be set at stable and easy-to-observe locations and marked with obvious signs;

[0031] The round trip measurement method is adopted, that is, each measurement section is observed twice, starting from a known point, observing forward along the measurement route, conducting a forward measurement, and returning from the end point to the known point, conducting a return measurement;

[0032] When the optical level is used to measure forward, the order of the odd-numbered stations is "back-front-front-back", and the order of the even-numbered stations is "front-back-back-front". When the digital level is used to measure forward and backward, both the odd-numbered and even-numbered stations are observed in the order of "back-front-front-back".

[0033] Record the observation data of each station, including the level rod reading, line of sight length, front and rear line of sight difference, and collect the temperature and wind environment conditions during the observation and indicate them in the record;

[0034] Conduct preliminary inspection of field observation data to check whether the data is complete and accurate and whether there are any abnormal values. If there are any abnormal values, they need to be re-measured or eliminated;

[0035] The leveling adjustment method is used to process the observation data and calculate the elevation value and accuracy index of each monitoring point;

[0036] Based on the adjustment calculation results, the vertical deformation of the artificial island surface is analyzed to determine whether the artificial island has deformation phenomena such as settlement and uplift, and deformation maps and deformation curves are drawn to intuitively display the deformation trends and characteristics.

[0037] A further improvement of the technical solution of the present invention is that in the InSAR monitoring module, the process of acquiring the deformation information of the target is as follows:

[0038] Use radar systems to obtain SAR images of the same target object from different spatial locations. SAR images record the intensity and phase information of the object. The radar transmits microwave signals and receives echo signals reflected by the object to form SAR images. Radar systems are usually mounted on satellites or aircraft and can cover a large area.

[0039] Preprocess the acquired SAR images to eliminate the influence of atmospheric and terrain factors on the radar echo signal strength, including denoising, geometric correction, and radiation correction, to improve the accuracy of subsequent processing. Atmospheric correction is used to correct the influence of the atmosphere on the propagation path of SAR signals to ensure the accuracy of phase information. Denoising is used to remove noise in the image and improve data quality.

[0040] Register SAR images acquired at different spatial locations so that they are aligned in the same geographic coordinate system;

[0041] Using the registered SAR image, an interference pattern is generated by calculating the pixel-level phase difference, where the interference pattern contains surface deformation information. The interference pattern is phase unwrapped to restore the true phase change value. Since the phase information in the interference pattern is wrapped in the interval [-π, π), phase unwrapping is required to restore the true phase change value. InSAR technology uses radars located at different spatial positions to observe the same target object, obtain two or more SAR images, perform interference processing, and obtain the elevation or deformation information of the target through the interference phase difference of the two echo signals of the same target. The phase in the interferometric measurement includes:

[0042] ;

[0043] in, represents the flat earth phase, or the reference plane phase, represents the terrain phase, represents the deformation phase, represents the atmospheric phase, represents the noise phase;

[0044] The unwrapped phase information is used in combination with radar system parameters and geometric relationships to calculate the surface deformation information, which includes vertical deformation of settlement and uplift, as well as horizontal displacement. The calculated surface deformation information is then evaluated for accuracy to ensure the reliability of the results.

[0045] A further improvement of the technical solution of the present invention is that in the data processing module, the deformation signal-to-noise ratio is improved by:

[0046] For every two SAR images, calculate their spatial baseline and temporal baseline, where the spatial baseline is the length of the baseline perpendicular to the line of sight, and the temporal baseline is the time interval between two observations, so that the baseline generated by every two SAR images is within the preset threshold, indicating whether the images are coherent, and generate the optimal spatiotemporal baseline connection map and interference pair connection map, and the middle image of the time series is selected as the main reference image;

[0047] Evaluate and prepare precise orbit files and external DEM files for each image, use SRTMDEM with a resolution of 30m, remove terrain effects, make all differential interferograms based on existing interferometric processing methods, and use GPU-assisted InSAR processing methods to improve processing efficiency, including geometric registration, resampling, and enhanced spectral diversity correction;

[0048] In view of the complex structures and dense vegetation coverage in some areas of artificial islands, the SBAS spatiotemporal filtering algorithm is used to remove the atmospheric phase error, obtain a high-precision deformation field that is continuous in time and space, and restore the phase value in the interference pattern to the true value through phase unwrapping processing;

[0049] In order to reduce the orbit residuals caused by the possible inaccurate ephemeris parameters and tropospheric effects in the interferogram, before executing Stacking, GACOS is used to assist in atmospheric delay error and long wavelength error correction. Redundant observations are used, and after Stacking processing, the least squares method is used to perform deformation inversion on the unwrapped interferogram to estimate and weaken the atmospheric phase error and terrain error, thereby improving the deformation signal-to-noise ratio.

[0050] The average deformation rate is calculated based on the least squares method through high-pass and low-pass filters to obtain the deformation rate map, and the time series cumulative deformation is obtained using the singular value decomposition algorithm to obtain the time series cumulative deformation map;

[0051] The obtained time series deformation map and deformation rate map are converted from the radar coordinate system to the geographic coordinate system.

[0052] A further improvement of the technical solution of the present invention is that in the data fusion analysis module, the process of obtaining the comprehensive deformation result is:

[0053] Collect GNSS PPP benchmark point data, leveling monitoring point data and InSAR settlement monitoring point data. GNSS PPP benchmark point data can accurately reflect the three-dimensional position changes of the surface. The data includes satellite observation data, precise ephemeris and clock error, etc., which are used to calculate the precise position of the benchmark point. Leveling monitoring point data refers to the vertical displacement data collected from the leveling monitoring point.

[0054] Transform the data of GNSS PPP benchmark points, leveling monitoring points and InSAR subsidence monitoring points into the same coordinate frame to ensure the spatial consistency of the data;

[0055] Compare the GNSS PPP benchmark data with the data of the leveling monitoring points to verify the consistency of the two in vertical displacement monitoring. Compare the InSAR subsidence monitoring data with the GNSS PPP and leveling data in space and time to analyze the consistency and continuity of the data.

[0056] After PPP solution, the three-dimensional coordinates of the reference point are obtained After the leveling measurement adjustment calculation, the vertical coordinates of each leveling monitoring point are obtained. According to the PPP reference points, the corresponding points on the SAR image are found and the transformation relationship between the two is established. The deformation variable in the InSAR monitoring line of sight is projected to the vertical direction to obtain the vertical deformation rate of the artificial island surface.

[0057] The PPP benchmark point data and the vertical coordinates of the leveling monitoring points were compared and analyzed with the InSAR line-of-sight data, and the surface settlement process of the artificial island was obtained by coupling PPP-InSAR.

[0058] A further improvement of the technical solution of the present invention is that: the comprehensive processing flow of coupling PPP-InSAR to obtain the surface settlement process of the artificial island is:

[0059] Through a small amount of PPP monitoring data, combined with the optimal algorithm inversion, the parameters of the artificial island regional probability integral method are obtained;

[0060] Combined with the time series data of surface monitoring points, the Levenberg-Marquardt algorithm is used to obtain the Gompertz time function model parameters, and the Gompertz-PIM surface settlement spatiotemporal model is constructed by combining the obtained artificial island regional probability integral method parameters.

[0061] Select N+1 SAR images covering the entire artificial island area and perform pairwise difference processing on them according to the time series to obtain the phases of N interference pairs;

[0062] The surface subsidence model value corresponding to the imaging time of N+1 SAR images is calculated through the Gompertz-PIM model, and the corresponding simulation phase is generated;

[0063] The Kalman filter algorithm is used to fuse InSAR and model phases;

[0064] The fused phase is unwrapped, and the unwrapped result is smoothed using the Loess algorithm to obtain the final surface settlement fusion result.

[0065] A further improvement of the technical solution of the present invention is that in the deformation result module, the process of evaluating the stability of the artificial island is:

[0066] Obtain comprehensive deformation result data from the data fusion analysis module, including spatial position, timestamp and corresponding deformation value;

[0067] For each monitoring point, calculate its deformation rate during the monitoring period. The deformation rate is obtained by calculating the displacement change per unit time.

[0068] Perform spatial interpolation on the deformation rate, grid the interpolation results, generate a continuous deformation rate map, and store it in the form of raster data;

[0069] Use GIS to visualize the deformation rate map and set the corresponding color band and scale to make the deformation rate map easy to interpret;

[0070] Select specific feature points on the artificial island for analysis. The feature points are known important buildings, infrastructure or potential risk points. Extract all deformation data of the selected feature points during the monitoring period from the comprehensive deformation result data. The data includes timestamps and corresponding deformation values.

[0071] Perform statistical analysis on the extracted time series data, plot the time series deformation results into a scatter plot to show the deformation trend over time, and mark important time nodes and deformation events in the graph for easy interpretation and comparison;

[0072] Based on the deformation rate diagram and time series deformation results, explain the deformation characteristics of the artificial island during the monitoring period and analyze the causes of deformation;

[0073] Based on the deformation data and interpretation results, the stability of the artificial island is evaluated to determine whether the artificial island is in a stable state or has potential risks, and areas with abnormal deformation rates or poor deformation trends are identified as potential risk areas;

[0074] Prepare deformation result analysis report and put forward corresponding monitoring, early warning and response measures suggestions based on the stability assessment results.

[0075] In a second aspect, a method for monitoring the subsidence of an offshore artificial island is implemented based on a subsidence monitoring system for an offshore artificial island, and includes the following steps:

[0076] Step 1: Use GNSS receivers to collect carrier phase and code pseudorange data, obtain SAR images through radar systems, and perform preprocessing, including denoising, geometric correction, radiation correction, etc.

[0077] Step 2: According to the terrain, geological conditions and monitoring requirements of the artificial island, evenly distribute the monitoring points to form a closed-loop measurement route, perform leveling in a round-trip measurement manner, record the data and conduct preliminary inspection;

[0078] Step 3, using SBAS-InSAR technology to process SAR images, generate interferograms, perform phase unwrapping and atmospheric and terrain error correction, and perform adjustment calculation on the leveling data to obtain the elevation value and accuracy index of each monitoring point;

[0079] Step 4: fuse the data of GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points, unify them into the same coordinate frame, and compare and verify them with each other;

[0080] Step 5: Using the data fusion analysis module, the deformation results are integrated to obtain the deformation rate diagram of the entire artificial island, and the time series deformation results of any feature point during the monitoring period are provided;

[0081] Step 6: Based on the comprehensive analysis results, evaluate the stability of the artificial island, identify potential safety hazards, provide deformation result analysis report and deformation data, and formulate corresponding management measures and monitoring plans.

[0082] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0083] The present invention provides a system and method for monitoring the subsidence of an offshore artificial island. By integrating GNSS PPP, leveling and InSAR technology, full-coverage subsidence monitoring from point to line to surface is achieved, overcoming the limitations of a single monitoring technology, improving the comprehensiveness, continuity and high precision of monitoring. The system can timely detect and warn of the subsidence risk of the artificial island, ensure the safety of buildings and infrastructure on the island, reduce economic and property losses, and protect people's lives.

[0084] The present invention provides a system and method for monitoring the settlement of an offshore artificial island. By comprehensively using a variety of high-precision monitoring technologies such as GNSS, leveling, and InSAR, large-scale, continuous, and high-precision deformation monitoring of the surface of the artificial island is achieved. The InSAR technology uses the phase difference of radar signals to measure tiny deformations of the surface, captures changes such as settlement, uplift, and horizontal displacement of the artificial island, and provides important data support for overall stability assessment. Compared with traditional ground monitoring methods, the InSAR technology can provide a wider coverage range, is not limited by terrain and climatic conditions, and makes monitoring more comprehensive and continuous.

[0085] The present invention provides a system and method for monitoring the subsidence of an artificial island at sea. By integrating the GNSS PPP technology, using the carrier phase and code pseudorange data collected by a GNSS receiver, combined with high-precision satellite orbit and clock error data, and using a model correction method to reduce errors, high-precision positioning is achieved, and a calculation benchmark is provided for leveling and InSAR monitoring, thereby ensuring the accuracy and reliability of the monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0087] Figure 1 It is a module diagram of the present invention. DETAILED DESCRIPTION

[0088] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0089] Embodiment 1, as Figure 1 As shown, the present invention provides an offshore artificial island settlement monitoring system, including a monitoring management center, the monitoring management center is communicatively connected with a GNSS PPP module, a leveling module, an InSAR monitoring module, a data processing module, a data fusion analysis module and a deformation result module, wherein the modules are connected by electrical signals;

[0090] The GNSS PPP module uses GNSS receivers to collect carrier phase and code pseudorange data, combines high-precision satellite orbit and clock error data, and reduces errors through model correction methods to achieve high-precision positioning. It provides a high-precision spatial positioning benchmark as a starting benchmark for leveling and InSAR monitoring to ensure the accuracy and reliability of monitoring results. The GNSS receiver simultaneously receives carrier phase and code pseudorange observations from multiple satellites, and uses IGS to obtain high-precision satellite orbit and clock error data to reduce satellite orbit and clock error; based on carrier phase and code pseudorange observations, combined with high-precision satellite orbit and clock error data, GNSS is constructed. PPP observation equation, the application of model correction method to reduce the impact of various error sources on the positioning results, including the total tropospheric delay effect, ionospheric delay correction, receiver and satellite clock error correction, tidal correction, among which, the tropospheric delay correction uses the tropospheric delay model to estimate and correct the delay caused by the signal passing through the atmosphere, the ionospheric delay correction uses dual-frequency signals to reduce the impact of the ionosphere on the signal, the receiver and satellite clock error correction uses high-precision satellite clock error data to correct the time difference between the receiver and the satellite, and the tidal correction corrects the deformation caused by the earth's tide, including the solid tide and the ocean tide load effect. The expression for calculating the total tropospheric delay effect is:

[0091] ;

[0092] in, is the total tropospheric delay on the propagation path; the component of the total tropospheric delay in the zenith direction is , ; , The mapping functions corresponding to dry and wet delays, such as NMF function and VMF function, are used. The dual-frequency ionospheric elimination linear combination model is used to reflect the geometric relationship between the observed quantity and the unknown parameters, and precise point positioning is performed. The combined observation values ​​are analyzed to eliminate the influence of the ionosphere on the positioning accuracy. The three-dimensional coordinates of the receiver are calculated by the precise point positioning algorithm using the corrected data. The calculated three-dimensional coordinates are verified to evaluate the positioning accuracy to ensure that the monitoring requirements are met. The calculated high-precision three-dimensional coordinates are used as the starting reference point for leveling and InSAR monitoring, providing a reference for other monitoring modules.

[0093] Furthermore, the expression of the GNSS PPP observation equation is:

[0094] ;

[0095] ;

[0096] in, , represent the station and satellite respectively, is the speed of light, is the star station distance; , are the code pseudorange and phase pseudorange observation values ​​respectively, is the carrier phase observation value, is the receiver clock error, is the satellite clock error, , are the tropospheric and ionospheric delay corrections, is the carrier phase ambiguity, , is the corresponding observation noise;

[0097] The expression for precise point positioning is:

[0098] ;

[0099] ;

[0100] in, , are the phase and code pseudorange combined observation values, is the frequency, , They are and The frequency of the carrier phase observations; , Respectively , Frequency raw pseudorange observations; , Respectively , Frequency phase observations.

[0101] The leveling module adopts a round-trip measurement method to evenly distribute monitoring points to form a closed-loop measurement route, and performs data verification and adjustment calculations to obtain deformation results, provide deformation data in the vertical direction of the artificial island surface, and verify with GNSSPPP and InSAR monitoring results to improve the comprehensiveness and accuracy of monitoring. According to the terrain, geological conditions and monitoring needs of the artificial island, evenly distribute monitoring points to form a closed-loop measurement route. Monitoring points should be set in stable and easy-to-observe locations and set with obvious signs. The round-trip measurement method is adopted, that is, each measurement section is observed twice, starting from a known point, observing forward along the measurement route, conducting a forward measurement, and returning from the end point to the known point for observation, and conducting a return measurement. When the optical level is used for forward measurement, the order of odd-numbered stations is "back-front-front-back". The sequence of even-numbered stations is "front-rear-rear-front". The digital level is used to measure odd-numbered stations and even-numbered stations in the order of "rear-front-front-rear". The observation data of each station is recorded, including the level rod reading, line of sight length, and front and rear line of sight difference. The temperature and wind environment conditions during the observation are collected and noted in the records. A preliminary inspection is carried out on the field observation data to check whether the data is complete and accurate, and whether there are any abnormal values. If there are any abnormal values, they need to be re-measured or eliminated. The leveling adjustment method is used to process the observation data, calculate the elevation value of each monitoring point and its accuracy index, and analyze the deformation of the artificial island in the vertical direction based on the adjustment calculation results to determine whether the artificial island has deformation phenomena such as settlement and uplift, and draw deformation maps and deformation curves to intuitively display the deformation trends and characteristics;

[0102] The InSAR monitoring module uses InSAR technology to observe the same target object using radars at different spatial positions, obtain SAR images and perform interference processing to obtain the deformation information of the target, thereby realizing large-scale, continuous and high-precision deformation monitoring of the surface of the artificial island. It can capture tiny surface deformations and provide important data support for overall stability assessment. The radar system is used to obtain SAR images of the same target object from different spatial positions. The SAR image records the intensity and phase information of the object. The radar transmits microwave signals and receives the echo signals reflected by the object to form a SAR image. The radar system is usually mounted on satellites or aircraft and can cover a large area. Preprocessing is performed to eliminate the influence of atmospheric and terrain factors on the radar echo signal intensity, including denoising, geometric correction, and radiation correction, to improve the accuracy of subsequent processing. Atmospheric correction is used to correct the influence of the atmosphere on the propagation path of SAR signals to ensure the accuracy of phase information. Denoising is used to remove noise in the image and improve data quality. SAR images acquired at different spatial locations are registered so that they are aligned in the same geographic coordinate system. The registered SAR images are used to generate an interference map by calculating the pixel-level phase difference, where the interference map contains surface deformation information. The interference map is phase unwrapped to restore the true phase change value. Since the phase information in the interference map is wrapped in the [-π, π) interval, phase unwrapping is required to restore the true phase change value. InSAR technology uses radars located at different spatial positions to observe the same target object, obtain two or more SAR images, perform interference processing, and obtain the elevation or deformation information of the target through the interference phase difference of the two echo signals of the same target. The phase in interferometric measurement includes:

[0103] ;

[0104] in, represents the flat earth phase, or the reference plane phase, represents the terrain phase, represents the deformation phase, represents the atmospheric phase, represents the noise phase;

[0105] The unwrapped phase information is used in combination with radar system parameters and geometric relationships to calculate the surface deformation information, which includes vertical deformation of settlement and uplift, as well as horizontal displacement. The calculated surface deformation information is then evaluated for accuracy to ensure the reliability of the results.

[0106] The data processing module uses the time series InSAR technology based on the SBAS method to estimate and weaken the atmospheric phase error and terrain error through the least square method and singular value decomposition algorithm, improve the deformation signal-to-noise ratio, and improve the deformation monitoring accuracy. The original N+1 SAR images covering a specific area generate M expansion interferograms within a specific range by assuming a time-space baseline. Points with an average phase coherence greater than a certain threshold are considered to be high coherence points. The unfolded phase (corresponding to the two moments and) of a high coherence point of the unfolded interferogram is expressed as follows: ;

[0107] in, is the phase value of the high coherence point in the differential interference pattern, , express and The interference phase generated by the images taken at each moment, and represents the cumulative displacement of the radar line of sight (LOS) at and relative to the start time, is the radar wavelength, is the elevation residual phase caused by the inaccuracy of the DEM; the noise phase (such as atmospheric phase masking and unwrapping error) is expressed as , after removing the residual elevation phase, this phase is solved to solve for the velocity term. The parameters that need to be solved are as follows:

[0108] ;

[0109] in, is the average phase velocity of the two acquisition times; Indicates The average phase velocity, For the The phase of a moment; Refers to a moment;

[0110] No. The phase of the unfolded interference pattern can be written as:

[0111] ;

[0112] in, is the phase of the I-th unfolded interference pattern, refers to the Pth moment, represents the Pth average phase velocity;

[0113] The phase of all interferograms is expressed in the above form, and the combined expression is expressed in the error equation as:

[0114] ;

[0115] in, is a matrix of dimension M×N, W is a vector of unknown deformation phase values, represents the interference phase value vector. If a single interference pattern subset is formed, the least square method is used to solve the deformation rate. When two or more interference pattern subsets are created, the singular value decomposition algorithm with the minimum norm condition is introduced to obtain the deformation rate.

[0116] For every two SAR images, calculate their spatial baseline and time baseline so that the baseline generated by every two SAR images is within the preset threshold, indicating whether the images are coherent, generate the optimal space-time baseline connection diagram and interference pair connection diagram, and the intermediate image of the time series is selected as the main reference image. Evaluate and prepare the precise orbit file and external DEM file of each image, use SRTM DEM with a resolution of 30m to remove the terrain effect, and make all differential interference diagrams based on the existing interference processing method. Use GPU-assisted InSAR processing methods to improve processing efficiency, including geometric alignment, resampling and enhanced spectral diversity correction. In view of the complex structures of artificial islands and dense vegetation coverage in some areas, the SBAS space-time filtering algorithm is used to remove the atmospheric phase error, and a high-precision deformation field that is continuous in time and space is obtained. The phase value in the interference diagram is restored to the true value through phase unwrapping processing. In order to reduce the orbit residuals caused by possible inaccurate ephemeris parameters and tropospheric effects in the interference diagram, the GPU-assisted InSAR processing method is used to improve the processing efficiency. Before stacking, GACOS is used to assist in atmospheric delay error and long wavelength error correction. Redundant observations are used, and after stacking processing, the least square method is used to perform deformation inversion on the unwrapped interferogram, and the atmospheric phase error and terrain error are estimated and weakened to improve the deformation signal-to-noise ratio. The average deformation rate is calculated based on the least square method through high-pass and low-pass filters to obtain the deformation rate map, and the singular value decomposition algorithm is used to obtain the time series cumulative deformation. The time series deformation map and deformation rate map are converted from the radar coordinate system to the geographic coordinate system.

[0117] The data fusion analysis module is used to fuse the data of GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points, unify them into the same coordinate frame, compare and verify them, and obtain comprehensive deformation results. Through the fusion of multi-source data, the accuracy and reliability of the monitoring results are improved, the stability of the artificial island is fully reflected, and potential safety hazards are discovered in time. The GNSS PPP benchmark point data, leveling monitoring point data and InSAR settlement monitoring point data are collected. The GNSS PPP benchmark point data can accurately reflect the three-dimensional position changes of the surface. The data includes satellite observation data, precise ephemeris and clock error, etc., which are used to calculate the precise position of the benchmark point; the leveling monitoring point data represents the vertical displacement data collected from the leveling monitoring point. The data of the GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points are converted into the same coordinate frame to ensure the spatial consistency of the data. The GNSS PPP benchmark point data is compared with the leveling monitoring point data to verify the consistency of the two in vertical displacement monitoring. The InSAR settlement monitoring data is compared with the GNSS Compare PPP and leveling data in space and time to analyze the consistency and continuity of the data. After PPP solution, the three-dimensional coordinates of the reference point are obtained. After the leveling measurement adjustment calculation, the vertical coordinates of each leveling monitoring point are obtained. According to the PPP benchmark points, the corresponding points on the SAR image are found and the conversion relationship between the two is established. The deformation in the line of sight of InSAR monitoring is projected to the vertical direction to obtain the vertical deformation rate of the artificial island surface. The PPP benchmark point data and the vertical coordinates of the leveling monitoring points are used to compare and analyze the InSAR line of sight data, and the surface settlement process of the artificial island is obtained by coupling PPP-InSAR.

[0118] Furthermore, the comprehensive processing flow of coupling PPP-InSAR to obtain the surface subsidence process of the artificial island is as follows:

[0119] Through a small amount of PPP monitoring data, combined with the optimal algorithm inversion, the parameters of the probability integral method of the artificial island area are obtained. Combined with the time series data of the surface monitoring points, the Levenberg-Marquardt algorithm is used to obtain the parameters of the Gompertz time function model. Combined with the obtained parameters of the probability integral method of the artificial island area, the Gompertz-PIM surface settlement spatiotemporal model is constructed. N+1 SAR images covering the entire artificial island area are selected to perform pairwise difference processing on them according to the time series to obtain the phases of N interference pairs. The surface settlement model value corresponding to the imaging time of the N+1 SAR images is calculated through the Gompertz-PIM model, and the corresponding simulation phase is generated. The Kalman filter algorithm is used to fuse the InSAR and model phases, and the fused phase is unwrapped. The Loess algorithm is used to smooth the unwrapped result to obtain the final surface settlement fusion result.

[0120] The deformation result module is used to analyze and process the comprehensive deformation results obtained by the data fusion analysis module, obtain the deformation rate map of the entire artificial island, provide the time series deformation results of any feature point during the monitoring period, provide detailed deformation data for decision makers, and help evaluate the stability of the artificial island. The comprehensive deformation result data, including spatial position, timestamp and corresponding deformation value, are obtained from the data fusion analysis module. For each monitoring point, its deformation rate during the monitoring period is calculated. The deformation rate is obtained by calculating the displacement change per unit time. The deformation rate is spatially interpolated, and the interpolation results are gridded to generate a continuous deformation rate map, which is stored in the form of raster data. The deformation rate map is visualized using GIS, and the corresponding color band and scale are set to make the deformation rate map easy to interpret. Specific feature points are selected on the artificial island for analysis. The feature points are known important Buildings, infrastructure or potential risk points, and extract all deformation data of the selected feature points during the monitoring period from the comprehensive deformation result data. The data includes timestamps and corresponding deformation values. Statistical analysis is performed on the extracted time series data, and the time series deformation results are plotted into a scatter plot to show the deformation trend over time. Important time nodes and deformation events are marked in the graph for easy interpretation and comparison. According to the deformation rate graph and time series deformation results, the deformation characteristics of the artificial island during the monitoring period are explained, and the causes of deformation are analyzed. Based on the deformation data and interpretation results, the stability of the artificial island is evaluated to determine whether the artificial island is in a stable state or has potential risks. Areas with abnormal deformation rates or poor deformation trends are identified as potential risk areas. A deformation result analysis report is compiled. According to the stability assessment results, corresponding monitoring, early warning and response measures are proposed.

[0121] Embodiment 2, as Figure 1As shown, based on Example 1, the present invention also provides a method for monitoring the settlement of an offshore artificial island, which is implemented based on a system for monitoring the settlement of an offshore artificial island, and includes the following steps:

[0122] Step 1: Use GNSS receivers to collect carrier phase and code pseudorange data, obtain SAR images through radar systems, and perform preprocessing, including denoising, geometric correction, radiation correction, etc.

[0123] Step 2: According to the terrain, geological conditions and monitoring requirements of the artificial island, evenly distribute the monitoring points to form a closed-loop measurement route, perform leveling in a round-trip measurement manner, record the data and conduct preliminary inspection;

[0124] Step 3, using SBAS-InSAR technology to process SAR images, generate interferograms, perform phase unwrapping and atmospheric and terrain error correction, and perform adjustment calculation on the leveling data to obtain the elevation value and accuracy index of each monitoring point;

[0125] Step 4: fuse the data of GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points, unify them into the same coordinate frame, and compare and verify them with each other;

[0126] Step 5: Using the data fusion analysis module, the deformation results are integrated to obtain the deformation rate diagram of the entire artificial island, and the time series deformation results of any feature point during the monitoring period are provided;

[0127] Step 6: Based on the comprehensive analysis results, evaluate the stability of the artificial island, identify potential safety hazards, provide deformation result analysis report and deformation data, and formulate corresponding management measures and monitoring plans.

[0128] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An offshore artificial island settlement monitoring system, comprising a monitoring management center, characterized in that: The monitoring and management center is communicatively connected with a GNSS PPP module, a leveling module, an InSAR monitoring module, a data processing module, a data fusion analysis module, and a deformation result module, wherein electrical signals are connected between the modules; The GNSS PPP module uses the GNSS receiver to collect carrier phase and code pseudorange data, combines high-precision satellite orbit and clock error data, reduces errors through model correction methods, and provides a spatial positioning benchmark as a starting benchmark for leveling and InSAR monitoring; The leveling module adopts a round-trip measurement method to evenly distribute monitoring points to form a closed-loop measurement line, and performs data verification and adjustment calculation to obtain deformation results; The InSAR monitoring module uses InSAR technology to observe the same target object using radars at different spatial positions, obtain SAR images and perform interference processing to obtain deformation information of the target. The process of obtaining the deformation information of the target is as follows: Use the radar system to obtain SAR images of the same target object from different spatial locations. The SAR images record the intensity and phase information of the object. Preprocess the acquired SAR images to eliminate the influence of atmospheric and terrain factors on the radar echo signal strength, including denoising, geometric correction, and radiation correction; Register SAR images acquired at different spatial locations so that they are aligned in the same geographic coordinate system; Using the registered SAR image, an interference pattern is generated by calculating the pixel-level phase difference, where the interference pattern contains surface deformation information. The interference pattern is phase unwrapped to restore the true phase change value. Since the phase information in the interference pattern is wrapped in the [-π,π) interval, phase unwrapping is required to restore the true phase change value. InSAR technology uses radars located at different spatial positions to observe the same target object, obtain two or more SAR images, perform interference processing, and obtain the elevation or deformation information of the target through the interference phase difference of the two echo signals of the same target. The phase in the interferometric measurement includes: in, represents the flat earth phase, or the reference plane phase, represents the terrain phase, represents the deformation phase, represents the atmospheric phase, represents the noise phase; The unwrapped phase information is used in combination with radar system parameters and geometric relationships to calculate the surface deformation information, which includes vertical deformation of settlement and uplift, as well as horizontal displacement, and the accuracy of the calculated surface deformation information is evaluated. The data processing module, based on the time series InSAR technology of the SBAS method, estimates and weakens the atmospheric phase error and terrain error through the least square method and singular value decomposition algorithm, improves the deformation signal-to-noise ratio, and improves the deformation monitoring accuracy. The original N+1SAR image covering a specific area generates M unfolding interferograms by assuming that the time-space baseline is within a specific range. Points with an average phase coherence greater than a certain threshold are considered to be high coherence points. The unfolding phase of the high coherence point of the i-th unfolding interferogram is expressed as follows: Among them, Δφ i (x,y) is the phase value of the high coherence point in the differential interference pattern, represents the interference phase generated by the images taken at time t1 and t2, d(t2,x,y) and d(t1,x,y) represent the cumulative displacement of the radar line of sight at the start time and relative to the start time, λ is the radar wavelength, is the elevation residual phase caused by the inaccuracy of the DEM; the noise phase is expressed as After removing the residual elevation phase, this phase is solved to solve for the velocity term. The parameters that need to be solved are as follows: Among them, W T is the average phase velocity of the two acquisition times; W N represents the Nth average phase velocity, φ N is the phase at the Nth moment; t N Refers to the Nth moment; The phase of the i-th unfolded interference pattern can be written as: Among them, Δφ i is the phase of the i-th unfolded interference pattern, t p Refers to the pth moment, W p represents the pth average phase velocity; The phase of all interferograms is expressed in the above form, and the combined expression is expressed in the error equation as: AW = Δφ; Where A is a matrix with dimension M×N, W is a vector of unknown deformation phase values, Δφ represents the interference phase value vector, if a single interference pattern subset is formed, the least square method is used to solve the deformation rate, when two or more interference pattern subsets are created, the singular value decomposition algorithm with the minimum norm condition is introduced to obtain the deformation rate, for every two SAR images, the spatial baseline and time baseline are calculated, so that the baseline generated by every two SAR images is within the preset threshold, indicating whether the image is coherent, and the optimal spatiotemporal baseline connection diagram and interference pair connection diagram are generated; Evaluate and prepare precise orbit files and external DEM files for each image, use SRTMDEM with a resolution of 30m, remove terrain effects, and produce all differential interferograms; The SBAS spatiotemporal filtering algorithm is used to remove the atmospheric phase error, obtain a high-precision deformation field that is continuous in time and space, and restore the phase value in the interference pattern to the true value through phase unwrapping processing; Through GACOS-assisted atmospheric delay error and long wavelength error correction, redundant observations are used, stacking is performed, and the least square method is used to perform deformation inversion on the unwrapped interferogram, estimate and weaken the atmospheric phase error and terrain error, and improve the deformation signal-to-noise ratio; The average deformation rate is calculated based on the least squares method through high-pass and low-pass filters to obtain the deformation rate map, and the time series cumulative deformation is obtained using the singular value decomposition algorithm to obtain the time series cumulative deformation map; The obtained time series deformation map and deformation rate map are converted from the radar coordinate system to the geographic coordinate system; The data fusion analysis module is used to fuse the data of the GNSS PPP benchmark points, the leveling monitoring points and the InSAR settlement monitoring points, unify them into the same coordinate frame, compare and verify them with each other, and obtain the comprehensive deformation results. In the data fusion analysis module, the process of obtaining the comprehensive deformation results is as follows: Collect GNSS PPP benchmark point data, leveling monitoring point data, and InSAR settlement monitoring point data; Convert the data of GNSS PPP benchmark points, leveling monitoring points and InSAR subsidence monitoring points into the same coordinate frame; Compare the GNSS PPP benchmark data with the data of the leveling monitoring points to verify the consistency of the two in vertical displacement monitoring. Compare the InSAR subsidence monitoring data with the GNSS PPP and leveling data in space and time to analyze the consistency and continuity of the data. After PPP solution, the three-dimensional coordinates (X, Y, Z) of the benchmark point are obtained, and the vertical coordinates (Z+ΔZ1, Z+ΔZ2, Z+ΔZ3, ..., Z+ΔZ n ), according to the laid PPP reference points, find the corresponding points on the SAR image and establish the transformation relationship between the two. The InSAR monitoring line of sight deformation is projected to the vertical direction to obtain the vertical deformation rate of the artificial island surface; The PPP benchmark point data and the vertical coordinates of the leveling monitoring points were compared and analyzed with the InSAR line-of-sight data, and the surface settlement process of the artificial island was obtained by coupling PPP-InSAR. The comprehensive processing flow of coupling PPP-InSAR to obtain the surface settlement process of the artificial island is as follows: Through a small amount of PPP monitoring data, combined with the optimal algorithm inversion, the parameters of the artificial island regional probability integral method are obtained; Combined with the time series data of surface monitoring points, the LM algorithm is used to obtain the Gompertz time function model parameters, and the Gompertz-PIM surface settlement spatiotemporal model is constructed by combining the obtained artificial island regional probability integral method parameters. Select N+1 SAR images covering the entire artificial island area and perform pairwise difference processing on them according to the time series to obtain the phases of N interference pairs; The surface subsidence model value corresponding to the imaging time of N+1 SAR images is calculated through the Gompertz-PIM model, and the corresponding simulation phase is generated; The Kalman filter algorithm is used to fuse InSAR and model phases; The fused phase is unwrapped, and the unwrapped result is smoothed using the Loess algorithm to obtain the final surface settlement fusion result; The deformation result module is used to analyze and process the comprehensive deformation results obtained by the data fusion analysis module, obtain the deformation rate diagram of the entire artificial island, provide the time series deformation results of any feature point during the monitoring period, and evaluate the stability of the artificial island. In the deformation result module, the process of evaluating the stability of the artificial island is as follows: Obtain comprehensive deformation result data from the data fusion analysis module, including spatial position, timestamp and corresponding deformation value; For each monitoring point, calculate its deformation rate during the monitoring period. The deformation rate is obtained by calculating the displacement change per unit time. Perform spatial interpolation on the deformation rate, grid the interpolation results, generate a continuous deformation rate map, and store it in the form of raster data; Use GIS to visualize the deformation rate map and set the corresponding color band and scale; Select specific feature points on the artificial island for analysis. The feature points are known important buildings, infrastructure or potential risk points. Extract all deformation data of the selected feature points during the monitoring period from the comprehensive deformation result data. The data includes timestamps and corresponding deformation values. Perform statistical analysis on the extracted time series data, plot the time series deformation results into a scatter plot to show the deformation trend over time, and mark important time nodes and deformation events in the graph; Based on the deformation rate diagram and time series deformation results, explain the deformation characteristics of the artificial island during the monitoring period and analyze the causes of deformation; Based on the deformation data and interpretation results, the stability of the artificial island is evaluated to determine whether the artificial island is in a stable state or has potential risks, and areas with abnormal deformation rates or poor deformation trends are identified as potential risk areas; Prepare deformation result analysis report and put forward corresponding monitoring, early warning and response measures suggestions based on the stability assessment results.

2. The offshore artificial island settlement monitoring system according to claim 1, characterized in that: In the GNSS PPP module, the process of acquiring the spatial positioning reference is as follows: The GNSS receiver simultaneously receives carrier phase and code pseudorange observations from multiple satellites, and uses the IGS to obtain high-precision satellite orbit and clock error data to reduce satellite orbit and clock error errors. Based on carrier phase and code pseudorange observations, combined with high-precision satellite orbit and clock error data, the GNSS PPP observation equation is constructed; The model correction method is applied to reduce the influence of various error sources on the positioning results, including the total tropospheric delay effect, ionospheric delay correction, receiver and satellite clock error correction, and tidal correction. Among them, the tropospheric delay correction uses the tropospheric delay model to estimate and correct the delay caused by the signal passing through the atmosphere. The ionospheric delay correction uses a dual-frequency signal to reduce the influence of the ionosphere on the signal. The receiver and satellite clock error correction uses high-precision satellite clock error data to correct the time difference between the receiver and the satellite. The tidal correction corrects the deformation caused by the earth's tide, including the solid tide and the ocean tide load effect. The expression for calculating the total tropospheric delay effect is: D trop =D dry ·M dry +D wet ·M wet ; Among them, Δ trop is the total tropospheric delay on the propagation path; the component of the total tropospheric delay in the zenith direction is Δ dry , Δ wet ;M dry 、M wet is the mapping function corresponding to dry and wet delay; The dual-frequency ionosphere-free linear combination model is used to reflect the geometric relationship between the observed quantity and the unknown parameters, and precise single-point positioning is performed. The combined observation values ​​are analyzed to eliminate the influence of the ionosphere on the positioning accuracy. Using the corrected data, the three-dimensional coordinates of the receiver are calculated through the precise point positioning algorithm, and the calculated three-dimensional coordinates are verified to evaluate the positioning accuracy to ensure that the monitoring requirements are met; The calculated high-precision three-dimensional coordinates are used as the starting reference points for leveling and InSAR monitoring, providing a reference for other monitoring modules.

3. The offshore artificial island settlement monitoring system according to claim 2, characterized in that: The expression of the GNSS PPP observation equation is: Among them, i and j represent the station and satellite respectively, c is the speed of light, is the star station distance; are the code pseudorange and phase pseudorange observation values ​​respectively, is the carrier phase observation value, δt i is the receiver clock error, δt j is the satellite clock error, δtrop j ,δdion j are the tropospheric and ionospheric delay corrections, respectively, and N j is the carrier phase ambiguity, ε P , ε L is the corresponding observation noise; The expression of the precise point positioning is: Among them, L IF , P IF They are the phase and code pseudorange combined observation values, f is the frequency, f1 and f2 are the frequencies of L1 and L2 carrier phase observation values, P1 and P2 represent the original pseudorange observation values ​​of f1 and f2 frequencies, L1 and L2 refer to the phase observation values ​​of f1 and f2 frequencies, respectively.

4. The offshore artificial island settlement monitoring system according to claim 3, characterized in that: In the leveling measurement module, the process of obtaining the deformation result is as follows: According to the artificial island's topography, geological conditions and monitoring requirements, the monitoring points are evenly distributed to form a closed-loop measurement line; The round trip measurement method is adopted, that is, each measurement section is observed twice, starting from a known point, observing forward along the measurement route, conducting a forward measurement, and returning from the end point to the known point, conducting a return measurement; When the optical level is used to measure forward, the order of odd-numbered stations is "back-front-front-back", and the order of even-numbered stations is "front-back-back-front". When the digital level is used to measure forward and backward, both odd-numbered and even-numbered stations are observed in the order of "back-front-front-back". Record the observation data of each station, including the level rod reading, line of sight length, front and rear line of sight difference, and collect the temperature and wind environment conditions during the observation and indicate them in the record; Conduct preliminary inspections on field observation data to check whether the data is complete, accurate, and whether there are any abnormal values; The leveling adjustment method is used to process the observation data and calculate the elevation value and accuracy index of each monitoring point; Based on the adjustment calculation results, the vertical deformation of the artificial island surface is analyzed, and deformation maps and deformation curves are drawn to intuitively display the deformation trends and characteristics.

5. A method for monitoring the subsidence of an artificial island at sea, implemented based on the system for monitoring the subsidence of an artificial island at sea according to any one of claims 1 to 4, characterized in that: The following steps are involved: Step 1: Use the GNSS receiver to collect carrier phase and code pseudorange data, obtain SAR images through the radar system, and perform preprocessing; Step 2: According to the terrain, geological conditions and monitoring requirements of the artificial island, evenly distribute the monitoring points to form a closed-loop measurement route, perform leveling in a round-trip measurement manner, record the data and conduct preliminary inspection; Step 3, using SBAS-InSAR technology to process SAR images, generate interferograms, perform phase unwrapping and atmospheric and terrain error correction, and perform adjustment calculation on the leveling data to obtain the elevation value and accuracy index of each monitoring point; Step 4: fuse the data of GNSS PPP benchmark points, leveling monitoring points and InSAR settlement monitoring points, unify them into the same coordinate frame, and compare and verify them with each other; Step 5: Using the data fusion analysis module, the deformation results are integrated to obtain the deformation rate diagram of the entire artificial island, and the time series deformation results of any feature point during the monitoring period are provided; Step 6: Based on the comprehensive analysis results, evaluate the stability of the artificial island, identify potential safety hazards, provide deformation result analysis report and deformation data, and formulate corresponding management measures and monitoring plans.

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