A crustal deformation research and analysis system and method based on GNSS data

Abstract

The application provides a crust deformation research and analysis system and method based on GNSS data, relates to the technical field of crust deformation monitoring and research, and comprises a hardware subsystem and a software subsystem; the hardware subsystem comprises a GNSS receiving module, a data storage module, a communication transmission module and a power supply module which cooperate with each other, and is used for realizing the collection, local storage and remote stable transmission of GNSS data; the software subsystem runs on a terminal device and comprises a data preprocessing module, a data solving module, an analysis module and a visual display module which are sequentially associated and cooperate with each other, and is used for realizing an integrated analysis process of GNSS original data preprocessing, data solving, crust deformation characteristic analysis and result visual display. The application can realize the integration of GNSS data collection, processing, analysis and display, improve the data processing efficiency, simplify the operation process, and provide convenient technical support for crust deformation research.

Description

Technical Field

[0001] This invention relates to the field of crustal deformation monitoring and research technology, and more specifically to a crustal deformation research and analysis system and method based on GNSS data. Background Technology

[0002] Crustal deformation is an important manifestation of tectonic movements, plate interactions, and the formation of geological hazards within the Earth. Monitoring and analyzing crustal deformation data is of great significance for studying geodynamic mechanisms and predicting geological hazards such as earthquakes. In recent years, GNSS technology has been gradually applied to the field of crustal deformation monitoring, but existing GNSS data products still have many shortcomings when applied to crustal deformation research: On the one hand, most products can only collect and output raw GNSS data, lacking a dedicated data processing module for crustal deformation research. They cannot effectively eliminate interference factors such as satellite orbital errors, ionospheric delay, and tropospheric delay, resulting in insufficient data accuracy and making it difficult to reflect the true situation of small crustal deformation (millimeter level).

[0003] On the other hand, existing products do not achieve integrated data acquisition, processing, and analysis. The data processing process is cumbersome, requiring researchers to use various third-party software for data conversion, correction, calculation, and analysis. This is difficult to operate, and the data formats of different software are incompatible, which can easily lead to data loss or error accumulation, reducing research efficiency.

[0004] Furthermore, the analysis results of existing products are mostly presented in the form of raw data or simple curves, lacking intuitive visualization and professional analysis capabilities, which makes it difficult to meet the needs of different researchers and hinders the promotion and application of crustal deformation research results.

[0005] Therefore, in view of the shortcomings of existing technologies, there is an urgent need for a technical solution that can achieve efficient acquisition, processing, analysis and intuitive display of GNSS data, so as to provide efficient and reliable technical support for crustal deformation research and promote the in-depth development of crustal deformation research. Summary of the Invention

[0006] In view of this, the present invention provides a crustal deformation research and analysis system and method based on GNSS data, which is applicable to scientific research and practical application scenarios related to crustal deformation, such as plate movement monitoring, earthquake precursor analysis, and geological disaster early warning. It can realize high-precision monitoring, data processing and analysis of small crustal deformations, and provide reliable technical support for crustal deformation research.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A crustal deformation research and analysis system based on GNSS data, comprising a hardware subsystem and a software subsystem; The hardware subsystem includes a GNSS receiving module, a data storage module, a communication transmission module, and a power supply module that work together to realize the acquisition, local storage, and stable remote transmission of GNSS data. The software subsystem runs on the terminal device and includes a data preprocessing module, a data calculation module, an analysis module, and a visualization module that are sequentially linked and coordinated. It is used to realize an integrated analysis process of GNSS raw data preprocessing, data calculation, crustal deformation characteristic analysis, and result visualization.

[0008] Optionally, the GNSS receiver module adopts a multi-frequency, multi-satellite receiver, supports the reception of signals from multiple constellations such as GPS, BeiDou, and GLONASS, and has an adjustable sampling rate range of 1Hz-50Hz. It has a built-in temperature compensation device to effectively capture satellite signals and obtain the raw three-dimensional coordinate data of the monitoring point.

[0009] Optionally, the data storage module uses a high-capacity solid-state storage chip with a storage capacity of no less than 1TB and has data encryption capabilities.

[0010] Optionally, the communication transmission module can flexibly switch between 4G and 5G transmission modes according to the network environment of the monitoring area, with a data transmission delay of no more than 10 seconds.

[0011] Optionally, the power supply module adopts a power supply method that combines solar power supply and battery backup, and has intelligent charging management function.

[0012] Optionally, the data preprocessing module is used to perform outlier removal, error correction, and format standardization on the raw GNSS data. Among them, error correction includes: satellite orbit error correction using IGS precise orbit products, ionospheric delay correction using a dual-frequency observation combination method to eliminate the influence of the ionosphere, and tropospheric delay correction using the Saastamoinen model, while eliminating receiver clock bias and antenna phase center deviation.

[0013] Optionally, the data processing module uses a combination of static and dynamic processing to process the preprocessed GNSS data. Static calculation is used to calculate long-term, slow crustal deformation. It is based on long-term continuous observation of no less than 24 hours and uses the least squares method to solve for the changes in the three-dimensional coordinates of the monitoring points. Dynamic calculation is used to calculate short-term transient crustal deformation, and the Kalman filter algorithm is combined to output displacement change data of monitoring points; The data processing module introduces the Helmert variance component estimation method for adaptive estimation of data weights and uses iterative weighted least squares estimation for outlier processing.

[0014] Optionally, the analysis module is used to analyze the crustal deformation characteristics and variation patterns of the crustal deformation data output by the data calculation module, and has four functions: time series analysis, spatial analysis, anomaly early warning and multi-source data fusion. The time series analysis specifically involves processing long-term monitoring data using wavelet analysis and principal component analysis to extract the periodic and trend changes in crustal deformation and determine the trend of crustal deformation. Spatial analysis specifically involves: combining the geographical location information of monitoring points to draw a spatial distribution map of crustal deformation, analyzing the deformation differences in different regions, and identifying areas of abnormal deformation; The anomaly warning is specifically designed as follows: a deformation threshold is set, and when the monitored deformation exceeds the deformation threshold, an early warning signal is automatically issued and an anomaly analysis report is generated. Multi-source data fusion specifically refers to supporting fusion analysis with InSAR data, gravity data, and other crustal deformation monitoring data.

[0015] Optionally, the visualization module supports displaying analysis results in the form of change curves, spatial distribution maps, and data tables, and has the functions of real-time updates, historical data backtracking, and data export.

[0016] A method for studying and analyzing crustal deformation based on GNSS data, applied to any of the above-mentioned systems for studying and analyzing crustal deformation based on GNSS data, includes the following steps: S1. Equipment Deployment and Data Acquisition: GNSS monitoring stations are deployed in the study area according to the needs of crustal deformation research, covering key locations in the study area; the hardware subsystem is activated, and satellite signals are acquired through the GNSS receiving module to obtain the raw three-dimensional coordinate data of the monitoring points. The data storage module stores the raw three-dimensional coordinate data locally, and the communication transmission module transmits the raw three-dimensional coordinate data to the software subsystem of the terminal equipment in real time. S2. Data Preprocessing: The data preprocessing module of the software subsystem performs outlier removal, multi-type error correction, and format standardization on the received raw 3D coordinate data to obtain standardized GNSS data. S3. Data Calculation: The data calculation module of the software subsystem performs static or dynamic calculations on standardized GNSS data to solve the three-dimensional displacement changes of the monitoring points in the longitude, latitude, and elevation directions, and obtain the original parameters of crustal deformation. S4. Deformation Analysis: The analysis module of the software subsystem performs time-series analysis, spatial analysis, and anomaly detection based on the original parameters of crustal deformation, extracts crustal deformation characteristics and variation patterns, identifies deformation anomaly areas, and generates analysis reports. S5. Results Display and Data Export: The visualization module of the software subsystem displays deformation data and analysis results in the form of change curves, spatial distribution maps, and data tables, and supports historical data backtracking and export of related data and analysis reports.

[0017] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a system and method for studying and analyzing crustal deformation based on GNSS data, which has the following beneficial effects: (1) High degree of integration and convenient operation: This invention integrates the entire process of data acquisition, preprocessing, calculation, analysis and display. It does not require the use of third-party software, which simplifies the operation process and reduces the difficulty of operation. Both professional researchers and non-professional researchers can quickly get started and use it. The visualization display method is intuitive and easy to understand, which facilitates data interpretation and results sharing.

[0018] (2) Wide applicability and high flexibility: This invention supports multi-constellation signal reception, adapts to different monitoring environments, and can achieve long-term stable monitoring in complex terrains such as high mountains, deserts, and remote areas; it supports two modes of static calculation and dynamic calculation, which can meet the research needs of long-term slow deformation and short-term transient deformation; at the same time, it supports multi-source data fusion, which can be combined with InSAR, gravity data, etc. to broaden the research dimensions.

[0019] (3) High practicality and application value: It can be widely used in plate movement monitoring, earthquake precursor analysis, geological disaster early warning and other fields. It can provide efficient and comprehensive data support and analysis tools for crustal deformation research, help researchers to understand the law of crustal deformation, provide scientific basis for earthquake prediction and geological disaster prevention and control, and has important scientific research value and practical application significance. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0021] Figure 1 A structural diagram of the crustal deformation research and analysis system based on GNSS data provided by this invention; Figure 2 The flowchart illustrates the crustal deformation research and analysis method based on GNSS data provided by this invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] To achieve end-to-end processing of GNSS data from acquisition to analysis, this invention discloses a crustal deformation research and analysis system based on GNSS data, such as... Figure 1 As shown, it includes hardware subsystems and software subsystems; The hardware subsystem includes a GNSS receiving module, a data storage module, a communication transmission module, and a power supply module that work together to realize the acquisition, local storage, and stable remote transmission of GNSS data, ensuring the continuity and reliability of data acquisition. The software subsystem runs on terminal devices such as computers and tablets. It includes a data preprocessing module, a data calculation module, an analysis module, and a visualization module that are linked together in sequence. It is used to realize an integrated analysis process of GNSS raw data preprocessing, data calculation, crustal deformation characteristic analysis, and result visualization.

[0024] Furthermore, the GNSS receiver module employs a multi-frequency, multi-satellite receiver, supporting signal reception from multiple constellations such as GPS, BeiDou, and GLONASS. The adjustable sampling rate ranges from 1Hz to 50Hz. It incorporates a built-in temperature compensation device to effectively capture satellite signals and acquire raw three-dimensional coordinate data (longitude, latitude, and elevation) of the monitoring point. The temperature compensation device reduces the impact of ambient temperature changes on signal reception, ensuring stable operation even in extreme environments such as high and low temperatures.

[0025] Furthermore, the data storage module uses a high-capacity solid-state storage chip with a storage capacity of no less than 1TB, capable of storing at least one year's worth of raw data; it also features data encryption to prevent data from being tampered with or leaked, ensuring data security.

[0026] Furthermore, the communication transmission module can flexibly switch between 4G and 5G transmission modes according to the network environment of the monitoring area, with a data transmission delay of no more than 10 seconds, enabling real-time or near-real-time data transmission and ensuring that researchers can obtain monitoring data in a timely manner.

[0027] Furthermore, the power supply module adopts a power supply method that combines solar power supply and battery backup. It is equipped with a large-capacity battery, which can ensure that the equipment can work continuously for more than 7 days in continuous rainy weather. At the same time, it has an intelligent charging management function, which can prevent the battery from being overcharged or over-discharged, extend the service life of the equipment, and is suitable for long-term field monitoring scenarios.

[0028] Furthermore, the data preprocessing module is used to remove outliers (such as errors caused by satellite signal interruption or interference), correct errors, and standardize the format of the raw GNSS data. This eliminates interference factors, improves data quality, and converts GNSS data of different formats into a unified format for easier subsequent processing and analysis. Among these, error correction includes: satellite orbit error correction using IGS precise orbit products, ionospheric delay correction using a dual-frequency observation combination method to eliminate ionospheric effects, and tropospheric delay correction using the Saastamoinen model. It also eliminates receiver clock bias and antenna phase center deviation.

[0029] Furthermore, the data processing module employs a combination of static and dynamic processing to process the preprocessed GNSS data. Static calculation is used to calculate long-term slow crustal deformation (such as plate movement). It is based on long-term continuous observation of no less than 24 hours and uses the least squares method to solve for the three-dimensional coordinate changes of the monitoring points. Dynamic calculation is used to calculate short-term transient crustal deformation (such as small deformation before an earthquake), and combines the Kalman filter algorithm to suppress noise and output displacement change data of monitoring points; The data processing module introduces the Helmert variance component estimation method for adaptive estimation of data weights and uses iterative weighted least squares estimation for outlier processing to improve the accuracy of the calculation, which can reach ±0.5mm.

[0030] Furthermore, the analysis module is used to analyze the crustal deformation characteristics and variation patterns of the crustal deformation data output by the data calculation module, and has four functions: time series analysis, spatial analysis, anomaly early warning and multi-source data fusion. The time series analysis specifically involves using wavelet analysis and principal component analysis to process long-term monitoring data, extracting periodic changes (such as tides and seasonal freeze-thaw cycles) and trend changes in crustal deformation, and determining the trend of crustal deformation. Spatial analysis specifically involves: combining the geographical location information of monitoring points to draw a spatial distribution map of crustal deformation, analyzing the deformation differences in different regions, and identifying areas of abnormal deformation; The anomaly warning specifically involves setting a deformation threshold. When the monitored deformation exceeds the deformation threshold, an early warning signal is automatically issued and an anomaly analysis report is generated, providing a reference for earthquake precursor analysis and geological disaster early warning. Multi-source data fusion specifically refers to supporting fusion analysis with InSAR data, gravity data, and other crustal deformation monitoring data to improve the comprehensiveness and accuracy of research.

[0031] Furthermore, the visualization module supports displaying analysis results in the form of change curves, spatial distribution maps, and data tables, and features real-time updates, historical data backtracking, and data export capabilities. Through this module, data processing and analysis results are presented in an intuitive and easy-to-understand format, facilitating viewing and interpretation by researchers. Researchers can use mouse operations to view deformation data and analysis results for any time period and any monitoring point. Processed data and analysis reports can be exported to common formats such as Excel, PDF, and TXT, facilitating subsequent research and results sharing.

[0032] based on Figure 1 The system shown in this embodiment also proposes a method for studying and analyzing crustal deformation based on GNSS data, such as... Figure 2 As shown, it includes the following steps: S1. Equipment Deployment and Data Acquisition: GNSS monitoring stations are deployed within the study area according to the needs of crustal deformation research, covering key locations in the study area (such as plate boundaries, active fault zones, and key earthquake-prone areas); the hardware subsystem is activated to acquire satellite signals and obtain the raw three-dimensional coordinate data of the monitoring points through the GNSS receiving module, which is stored locally by the data storage module, and the raw three-dimensional coordinate data is transmitted in real time to the software subsystem of the terminal equipment through the communication transmission module; S2. Data Preprocessing: The data preprocessing module of the software subsystem performs outlier removal, multi-type error correction, and format standardization on the received raw 3D coordinate data to obtain standardized GNSS data and eliminate the impact of various interference factors on data accuracy. S3. Data Calculation: The data calculation module of the software subsystem performs static or dynamic calculations on standardized GNSS data to solve the three-dimensional displacement changes of the monitoring points in the longitude, latitude, and elevation directions, and obtain the original parameters of crustal deformation. S4. Deformation Analysis: The analysis module of the software subsystem performs time-series analysis, spatial analysis, and anomaly detection based on the original parameters of crustal deformation, extracts crustal deformation characteristics and variation patterns, identifies deformation anomaly areas, and generates analysis reports. S5. Results Display and Data Export: The visualization module of the software subsystem displays deformation data and analysis results in the form of change curves, spatial distribution maps, and data tables. It also supports historical data backtracking and the export of relevant data and analysis reports for subsequent research or results reporting.

[0033] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The methods disclosed in the embodiments are described simply because they correspond to the systems disclosed in the embodiments; relevant details can be found in the method section.

[0034] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A crustal deformation research and analysis system based on GNSS data, characterized in that, Includes hardware subsystems and software subsystems; The hardware subsystem includes a GNSS receiving module, a data storage module, a communication transmission module, and a power supply module that work together to realize the acquisition, local storage, and stable remote transmission of GNSS data. The software subsystem runs on the terminal device and includes a data preprocessing module, a data calculation module, an analysis module, and a visualization module that are sequentially linked and coordinated. It is used to realize an integrated analysis process of GNSS raw data preprocessing, data calculation, crustal deformation characteristic analysis, and result visualization.

2. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The GNSS receiver module adopts a multi-frequency, multi-satellite receiver, supports the reception of signals from multiple constellations such as GPS, BeiDou, and GLONASS, and has an adjustable sampling rate range of 1Hz-50Hz. It has a built-in temperature compensation device to effectively capture satellite signals and obtain the raw three-dimensional coordinate data of the monitoring point.

3. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The data storage module uses a high-capacity solid-state storage chip with a storage capacity of no less than 1TB and has data encryption capabilities.

4. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The communication transmission module can flexibly switch between 4G and 5G transmission modes according to the network environment of the monitoring area, with a data transmission delay of no more than 10 seconds.

5. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The power supply module adopts a power supply method that combines solar power and battery backup, and has intelligent charging management function.

6. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The data preprocessing module is used to remove outliers, correct errors, and standardize the format of raw GNSS data. Among them, error correction includes: satellite orbit error correction using IGS precise orbit products, ionospheric delay correction using dual-frequency observation combination method to eliminate ionospheric effects, tropospheric delay correction using Saastamoinen model, and elimination of receiver clock error and antenna phase center deviation.

7. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The data processing module uses a combination of static and dynamic processing to process the preprocessed GNSS data. Static calculation is used to calculate long-term, slow crustal deformation. It is based on long-term continuous observation of no less than 24 hours and uses the least squares method to solve for the changes in the three-dimensional coordinates of the monitoring points. Dynamic calculation is used to calculate short-term transient crustal deformation, and the Kalman filter algorithm is combined to output displacement change data of monitoring points; The data processing module introduces the Helmert variance component estimation method for adaptive estimation of data weights and uses iterative weighted least squares estimation for outlier processing.

8. The crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The analysis module is used to analyze the crustal deformation characteristics and variation patterns of the crustal deformation data output by the data processing module. It has four functions: time series analysis, spatial analysis, anomaly early warning, and multi-source data fusion. The time series analysis specifically involves using wavelet analysis and principal component analysis to process long-term monitoring data, extracting the periodic and trend changes in crustal deformation, and determining the trend of crustal deformation. Spatial analysis specifically involves: combining the geographical location information of monitoring points to draw a spatial distribution map of crustal deformation, analyzing the deformation differences in different regions, and identifying areas of abnormal deformation; The anomaly warning is specifically as follows: set a deformation threshold, and when the monitored deformation exceeds the deformation threshold, an early warning signal will be automatically issued and an anomaly analysis report will be generated; Multi-source data fusion specifically refers to supporting fusion analysis with InSAR data, gravity data, and other crustal deformation monitoring data.

9. A crustal deformation research and analysis system based on GNSS data according to claim 1, characterized in that, The visualization module supports displaying analysis results in the form of change curves, spatial distribution maps, and data tables, and has the functions of real-time updates, historical data backtracking, and data export.

10. A method for studying and analyzing crustal deformation based on GNSS data, characterized in that, The system for studying and analyzing crustal deformation based on GNSS data, as described in any one of claims 1-9, includes the following steps: S1. Equipment Deployment and Data Acquisition: GNSS monitoring stations are deployed in the study area according to the needs of crustal deformation research, covering key locations in the study area; the hardware subsystem is activated, and satellite signals are acquired through the GNSS receiving module to obtain the raw three-dimensional coordinate data of the monitoring points. The data storage module stores the raw three-dimensional coordinate data locally, and the communication transmission module transmits the raw three-dimensional coordinate data to the software subsystem of the terminal equipment in real time. S2. Data Preprocessing: The data preprocessing module of the software subsystem performs outlier removal, multi-type error correction, and format standardization on the received raw 3D coordinate data to obtain standardized GNSS data. S3. Data Calculation: The data calculation module of the software subsystem performs static or dynamic calculations on standardized GNSS data to solve the three-dimensional displacement changes of the monitoring points in the longitude, latitude, and elevation directions, and obtain the original parameters of crustal deformation. S4. Deformation Analysis: The analysis module of the software subsystem performs time-series analysis, spatial analysis, and anomaly detection based on the original parameters of crustal deformation, extracts crustal deformation characteristics and variation patterns, identifies deformation anomaly areas, and generates analysis reports. S5. Results Display and Data Export: The visualization module of the software subsystem displays deformation data and analysis results in the form of change curves, spatial distribution maps, and data tables, and supports historical data backtracking and export of related data and analysis reports.

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