High slope GNSS monitoring data elevation correction method and system

Abstract

The application discloses a high-slope GNSS monitoring data elevation correction method and system, relates to the technical field of GNSS slope monitoring, and comprises the following steps: acquiring first observation data of a base station and second observation data of at least one GNSS measuring point, wherein the at least one GNSS measuring point has a height difference with the base station; calculating a change between each second observation data and the first observation data to obtain fluctuation data; establishing a height difference correction model based on all the fluctuation data; obtaining a correction value of a to-be-measured point by using the height difference correction model, and assigning the correction value to initial observation data of the to-be-measured point; and the system is a virtual device of the method. The correction method and system can establish an elevation correction model according to statistical relative change rules between the elevation GNSS measuring points and the base station, and can additionally correct the troposphere delay of other measuring points according to the model.

Description

Technical Field

[0001] This invention relates to the field of GNSS slope monitoring technology, and more specifically, to a method and system for correcting the elevation of GNSS monitoring data for high slopes. Background Technology

[0002] GNSS data is transmitted via radio waves. When passing through the atmosphere below 50km, the propagation speed of radio waves slows down and refraction occurs. The change in the propagation path of GNSS carriers due to media such as water vapor and air when passing through the troposphere is called tropospheric delay. Under normal circumstances, the effect of tropospheric delay can be reduced by differential mode.

[0003] In existing technologies, the differential positioning method is used to address the aforementioned tropospheric delay reduction problem. This means that during baseline processing, the atmospheric environment at both ends of the baseline can be considered relatively stable and highly correlated within a short period, and its influence can be largely eliminated through differential positioning. However, for GNSS monitoring of high slopes, since there will always be an elevation difference between the baseline point and the measuring point, the tropospheric delay between different elevations cannot be reduced.

[0004] In view of the above, this application is hereby submitted. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for correcting the elevation of GNSS monitoring data on high slopes. This method and system can establish an elevation correction model based on the statistical relative change law of data between the GNSS measuring points at different elevations and the base station by arranging at least one GNSS measuring point outside the deformation range of the slope. Based on this model, additional corrections can be made for the tropospheric delay at other measuring points.

[0006] The embodiments of the present invention are implemented as follows:

[0007] In a first aspect, a method for elevation correction of GNSS monitoring data for high slopes includes the following steps: acquiring first observation data from a base station and second observation data from at least one GNSS measuring point, wherein the at least one GNSS measuring point has a GNSS measuring point that forms an elevation difference with the base station, and wherein the GNSS measuring point is a monitoring point arranged outside the deformation range of the slope; calculating the change between each second observation data and the first observation data to obtain fluctuation data respectively; establishing an elevation difference correction model based on all fluctuation data; using the elevation difference correction model to obtain the correction value of the point to be measured, and assigning the correction value to the initial observation data of the point to be measured, wherein the point to be measured is a monitoring point that needs elevation correction.

[0008] In an optional implementation, both the first and second observation data include elevation data and meteorological data.

[0009] In an optional implementation, the meteorological data includes air pressure data, temperature data, and humidity data.

[0010] In an alternative implementation, the number of GNSS measuring points is associated with the elevation of the monitored high slope, where the first association refers to a positive correlation.

[0011] In an optional implementation, the elevation difference interval between adjacent GNSS measuring points ranges from 30 to 60 meters.

[0012] In an alternative implementation, the range of elevation difference intervals is adjusted based on parameters of tropospheric environmental change.

[0013] In an optional implementation, the number of GNSS measurement points is three.

[0014] In an optional implementation, establishing an elevation correction model based on all fluctuation data includes the following steps: performing correlation analysis on all fluctuation data to obtain multiple analysis results; and establishing an elevation correction model based on multiple analysis results using multiple regression or a neural network.

[0015] In an alternative implementation, the initial observation data of the point to be measured is obtained by differential positioning.

[0016] Secondly, a high slope GNSS monitoring data elevation correction system includes:

[0017] The first acquisition module is used to acquire first observation data of the base station and second observation data of at least one GNSS measuring point. Among the at least one GNSS measuring point, there is a GNSS measuring point that forms an elevation difference with the base station. The GNSS measuring point is a monitoring point arranged outside the slope deformation range.

[0018] The first calculation module is used to calculate the change between each second observation data and the first observation data, and obtain the fluctuation data respectively.

[0019] The first modeling module is used to build a height correction model based on all fluctuation data;

[0020] The second calculation module is used to obtain the correction value of the point to be measured using the elevation correction model, and assign the correction value to the initial observation data of the point to be measured, wherein the point to be measured is the measuring point that needs to be corrected for elevation.

[0021] The beneficial effects of the embodiments of the present invention are:

[0022] The elevation correction method and system for GNSS monitoring data of high slopes provided in this invention address the problem that the tropospheric delay caused by different elevations cannot be reduced in high slope deformation monitoring operations. It employs at least one GNSS measuring point at a different elevation outside the slope deformation range. An elevation correction model is established based on the statistical relative change patterns of data between these elevation GNSS measuring points and the base station. This model obtains the change patterns between monitoring data from different elevation measuring points and monitoring data from the base station. Based on these change patterns, the changes at other actual measuring points can be obtained. Thus, a correction amount is applied to the monitoring data at the actual measuring points, making the monitoring data more accurate. This achieves the purpose of additionally correcting the tropospheric delay at other actual measuring points. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating the main steps of the correction method provided in this embodiment of the invention;

[0025] Figure 2 A schematic diagram illustrating the scenario principle of the correction method provided in this embodiment of the invention;

[0026] Figure 3 A daily rainfall statistics chart provided for an embodiment of the present invention;

[0027] Figure 4 This is a diagram showing the elevation changes of measuring points with large elevation differences, provided in an embodiment of the present invention.

[0028] Figure 5 The displacement curve of J06 provided in the embodiment of the present invention;

[0029] Figure 6 An exemplary module diagram of the correction system provided in this embodiment of the invention.

[0030] Icons: 500 - Correction System; 501 - First Acquisition Module; 502 - First Calculation Module; 503 - First Modeling Module; 504 - Second Calculation Module. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0032] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0033] It should be understood that the terms "system," "device," and / or "module" used in this invention are methods for distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0034] As indicated in this invention and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0035] Flowcharts are used in this invention to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0036] Example

[0037] When GNSS satellite signals pass through the troposphere, they interact with neutral gases in the atmosphere. This can cause the satellite signal to slow down its propagation speed or bend its propagation path, resulting in a delay in the satellite signal reaching the receiver. The error caused by this process is known as tropospheric delay error.

[0038] Generally, the tropospheric refraction delay Ls can be represented by the sum of the products of the zenith delay of the dry and wet components and the corresponding mapping functions:

[0039] L s (ε)=p d md (ε)+p w m w (ε) (1)

[0040] In equation (1), p d p w These are the zenith delays for the dry and wet components, respectively. Generally, the zenith delays p for the dry and wet components are... d p w A relatively accurate Saastamoinen model can be obtained by correcting the model based on meteorological factors at the station. The dry component is relatively stable in both time and space, generally accounting for more than 80% of the total refraction. However, the wet component, which is related to water vapor, can vary by 6 to 8 cm / h over time in the zenith direction, which is 3 to 4 times that of the dry component. Regarding the tropospheric delay problem, we previously used the following methods to reduce it:

[0041] (1) Empirical model correction method: This method uses empirical models to reduce and correct tropospheric delay errors, such as the Hopfield model, the improved Hopfield model, the Saastamoinen model, the Black model, and the Chao model. However, all of these models require meteorological parameters as input for correction, which are not easy to obtain and may contain errors. Therefore, the accuracy of tropospheric delay correction is not high for small-area tropospheric delays.

[0042] (2) When solving the baseline, the tropospheric delay error is treated as an unknown: Using this method, when processing the data, we treat the zenith tropospheric delay as an unknown and estimate its precise value through adjustment calculation. The parameters can be determined by different methods depending on factors such as the length of the time period and the climate conditions during the observation period.

[0043] (3) Differential positioning method: During the baseline processing, it can be assumed that the atmospheric environment at both ends of the baseline is relatively stable in a short period of time, and its influence can be basically eliminated by differential positioning.

[0044] We found that the third method is less costly and relatively easier to implement. In high-precision baseline calculation, if the baseline length is short, the elevation difference between the two stations is small, and the atmospheric environment is stable during the observation period, the influence of tropospheric delay can be reduced through differential mode. GNSS baseline calculation uses relative positioning technology, also known as differential positioning. In its most basic case, receivers placed at both ends of the baseline perform synchronous observations to obtain observation data from the same epoch and satellite. The relative positions of the two ends of the baseline are then determined through data processing. Baseline calculation is a crucial step in high-precision GNSS measurement and positioning data processing. It utilizes carrier phase observation data obtained from synchronous observations at both ends of the baseline, establishes an error equation using the differential positioning principle, and then solves it using the least squares principle to finally obtain the three-dimensional coordinate vector of the baseline. GNSS deformation monitoring requires a reference station with known coordinates as the starting point. During GNSS baseline calculation, the reference point is used as a known quantity, and the coordinates of the monitoring point are obtained by calculating the difference in baseline coordinate vectors.

[0045] Accurate calculation of tropospheric delay requires obtaining pressure, temperature, and humidity along the GNSS signal propagation path. When the baseline distance is short and the elevation difference is small, differential methods can effectively reduce errors caused by the troposphere. However, for GNSS monitoring of high slopes, because there is always an elevation difference between the baseline and the measuring point, the tropospheric delay caused by differences in elevation cannot be reduced. Figure 2 As shown, the TNd1-TPg1 baseline can handle the delay error of troposphere 3 through differential analysis, but the delay errors of troposphere 1 and troposphere 2 cannot be canceled out. To address this issue, this embodiment provides a method for correcting the elevation of GNSS monitoring data for high slopes, which can achieve more accurate deformation monitoring between different elevation measuring points.

[0046] Please see Figure 1 This embodiment provides a method for correcting the elevation of GNSS monitoring data for high slopes, which includes the following steps:

[0047] S100: Acquire first observation data from the base station and second observation data from at least one GNSS measuring point. Among the at least one GNSS measuring point, there is a GNSS measuring point that forms an elevation difference with the base station. The GNSS measuring point is a monitoring point arranged outside the slope deformation range. This step indicates that subsequent calculations are performed by acquiring the observation data from the base station and the observation data from the added measuring points. For high slope scenarios, there will be an elevation difference between the actual measuring points within the deformed slope range and the base station measuring points. In this case, theoretical error calculation is performed by adding monitoring points outside the slope deformation range. This requires that among the at least one GNSS measuring point, there is a GNSS measuring point that forms an elevation difference with the base station, so as to facilitate the calculation of changes after the elevation difference exists.

[0048] It should be noted that the GNSS measuring points are monitoring points arranged outside the deformation range of the slope (different from the actual measuring points within the deformation range of the slope). The purpose is to keep the GNSS measuring points basically stable and without deformation trend in the vertical direction, so as to avoid vertical deformation errors that would affect the subsequent calculation results.

[0049] S200: Calculate the change between each of the second observation data and the first observation data to obtain fluctuation data; this step means comparing and analyzing the observation data of all GNSS measuring points with the observation data of the base station to obtain at least the change analysis results in elevation data. The elevation data is calculated using the tropospheric error reduction model and differential point calculation method described in (1), (2), and (3) above (e.g., by obtaining the original GNSS satellite data of the station and measuring point through observation, performing differential baseline calculation, and obtaining the elevation difference between the base station and the measuring point). The elevation comparison results obtained from calculating the elevations of all GNSS measuring points are statistically analyzed to facilitate step S300: Establishing an elevation difference correction model based on all the fluctuation data; this step means that after obtaining the fluctuation data of all GNSS measuring points at different elevations, an elevation difference correction model can be established based on these calculated data to characterize the degree of data fluctuation at measuring points at different elevations.

[0050] Specifically, in this embodiment, the step of establishing a height correction model based on all fluctuation data includes the following steps: performing correlation analysis (e.g., grey relational analysis, cluster analysis, etc.) on all the fluctuation data to obtain multiple analysis results; and establishing the height correction model based on the multiple analysis results using multiple regression or neural networks.

[0051] S400: Obtain the correction value for the measured point using the elevation correction model, and assign the correction value to the initial observation data of the measured point. The measured point is a monitoring point requiring elevation correction. In this step, the measured point is the actual measuring point within the deformed slope range, which is affected by tropospheric delay error and requires elevation correction. The change in elevation output by the elevation correction model is the correction value, which is then assigned to the initial observation data of the measured point. The initial observation data of the measured point is obtained using the differential positioning method.

[0052] By utilizing the above technical solutions, observation data from GNSS measuring points outside the actual measuring points, and observation data from base stations (e.g., through differential positioning), the calculated data of each GNSS measuring point relative to the base station can be obtained. By comparing and analyzing the results of these calculated data, the amount of change in the results caused by the tropospheric delay at different elevation points can be obtained. Based on the fluctuation in elevation data monitoring caused by this change, an elevation conversion model is established. The change law represented by this elevation conversion model is then applied to the data of the actual measuring points for correction, thereby obtaining more accurate and precise monitoring data.

[0053] In practical operations, we found that tropospheric delay error varies with environmental parameters such as temperature, humidity, and air pressure. Therefore, the aforementioned observation data also includes meteorological data; that is, both the first and second observation data include elevation data and meteorological data. In this embodiment, the meteorological data includes air pressure data, temperature data, and humidity data. Through this technical solution, the GNSS elevation correction model is correlated with environmental factors, which can be represented as a meteorological-GNSS elevation correction model. This model incorporates environmental parameters into the calculated influencing factors, making the calculation results more realistic and accurate. Therefore, when obtaining the first and second observation data, GNSS satellite data (for calculating elevation changes) and meteorological data (for calculating air pressure, temperature, and / or humidity changes) are obtained, allowing the correlation analysis to incorporate the influence of environmental parameters and ensuring the reliability of the calculated results.

[0054] Furthermore, the following considerations are taken into account regarding the number of GNSS monitoring points deployed: Theoretically, the more GNSS monitoring points deployed at different elevations, the more accurate the model will be; however, this will increase costs, especially the training sample set, and make the selection of GNSS monitoring point locations more complex. Therefore, for slopes with higher elevations, the number of GNSS monitoring points can be appropriately increased, and vice versa, balancing implementation difficulty and cost. In this embodiment, the number of GNSS monitoring points is positively correlated with the elevation of the monitored high slope, meaning that the higher the monitored high slope, the more GNSS monitoring points should be deployed.

[0055] Based on the above scheme, the elevation difference interval between adjacent GNSS measuring points is 30-60m, for example, 50m. Generally speaking, the horizontal elevation difference where the tropospheric environment changes significantly is within the range of about 70 meters. Therefore, by adopting this interval arrangement, the GNSS measuring point site selection is more representative, making it able to adapt to the characteristics mentioned above that take into account both implementation difficulty and cost.

[0056] Of course, in actual operations, considering the different geographical locations of different slopes, environmental parameters may change differently than usual. In such cases, the elevation difference interval range should be adjusted according to the tropospheric environmental change parameters. For example, for certain special scenarios, the interval range can be increased or decreased by detecting the specific values ​​of environmental change parameters, thereby ensuring that the slope deformation monitoring results are more reliable in these scenarios.

[0057] In different implementation methods, the number of GNSS measuring points can be determined according to the above method. In this embodiment, for representative high slope measurement, the number of GNSS measuring points is three, which can adapt to most slope deformation monitoring scenarios. Please refer to this again. Figure 2 Outside the high slope deformation monitoring range, GNSS monitoring points (TPg1, TPz1, and TPd1) are set up at high, medium, and low elevation locations respectively. These three points are basically stable, with no vertical deformation trend. Then, barometric pressure, temperature, and humidity sensors are set up at the GNSS measuring points and the base station to simultaneously collect GNSS satellite data and meteorological data. Through the GNSS monitoring data processing system, using the aforementioned tropospheric model and differential calculation method, the vertical deformation of each measuring point relative to the reference point is calculated. Then, the data between the measuring points and the reference station, including barometric pressure, temperature, humidity, and elevation fluctuations, are statistically analyzed. Finally, a correction model is established based on the barometric pressure, temperature, humidity, and elevation fluctuations (modeling input parameters are baseline elevation difference (dh), barometric pressure difference (dpa), temperature difference (dT), and humidity difference (dsd) between the base station and the measuring point; output is the GNSS elevation observation change values ​​of TPg1, TPz1, and TPd1). When correcting the actual measuring point values, the elevation correction value is calculated using this elevation difference correction model to correct the elevation of the measuring point.

[0058] The elevation correction method provided in this embodiment is an optimization of the traditional correction model and calculation method. The traditional GNSS tropospheric correction model and method do not have the need for monitoring in complex terrain environments. For high slopes, the elevation difference between GNSS monitoring points and base stations is usually as high as hundreds of meters.

[0059] Using a general tropospheric model and differential correction cannot effectively eliminate the effects of tropospheric delay. For measuring points with large elevation differences, the elevation difference can reach the centimeter level due to the influence of air pressure, temperature and humidity, causing the vertical deformation information to be buried in the system error.

[0060] As shown in Table 1 (Measurement Point Information Table), the distance and elevation difference between each GNSS measurement point and the base station in a certain project are statistically analyzed.

[0061] Measurement point information table

[0062] Table 1

[0063]

[0064] Combination Figures 3-5 As shown, for measuring points with larger elevation differences, the measured values ​​fluctuate more significantly (around 1 cm) from August to October due to humidity changes, and rise by about 3 cm between October and November. The greater the elevation difference, the more pronounced the rise. Afterward, rainfall decreases and humidity changes are small, resulting in relatively stable elevation deformation. Measuring points with smaller elevation differences, however, show no signs of such fluctuations or deformation.

[0065] This elevation correction method can improve the accuracy and reliability of slope GNSS monitoring in terms of deformation in the elevation direction.

[0066] This embodiment also provides a high slope GNSS monitoring data elevation correction system 500. Please refer to [link / reference]. Figure 6 This is a modular schematic diagram of the high slope GNSS monitoring data elevation correction system 500, mainly used to divide the high slope GNSS monitoring data elevation correction system 500 into functional modules according to the embodiments of the above method. For example, it can be divided into individual functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or software functional modules. It should be noted that the module division in this invention is illustrative and only represents one logical functional division; other division methods may be used in actual implementation. For example, in the case of dividing each functional module according to its corresponding function, Figure 6 The diagram shown is only a schematic of a system / device. The high slope GNSS monitoring data elevation correction system 500 may include a first acquisition module 510, a first calculation module 520, a first modeling module 530, and a second calculation module 540. The functions of each unit module are described below.

[0067] The first acquisition module 510 is used to acquire first observation data of the base station and second observation data of at least one GNSS measuring point. Among the at least one GNSS measuring point, there is a GNSS measuring point that forms an elevation difference with the base station. The GNSS measuring point is a monitoring point arranged outside the slope deformation range.

[0068] The first calculation module 520 is used to calculate the amount of change between each second observation data and the first observation data, and obtain fluctuation data respectively.

[0069] The first modeling module 530 is used to establish a height correction model based on all the said fluctuation data;

[0070] The second calculation module 540 is used to obtain the correction value of the point to be measured using the elevation correction model, and to assign the correction value to the initial observation data of the point to be measured, wherein the point to be measured is the measuring point that needs to be corrected for elevation.

[0071] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0072] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0073] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0074] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0075] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A method for correcting the elevation of GNSS monitoring data for high slopes, characterized in that, Includes the following steps: Acquire first observation data from a base station and second observation data from at least one GNSS measuring point, wherein at least one of the GNSS measuring points has a GNSS measuring point that forms an elevation difference with the base station, and wherein the GNSS measuring point is a monitoring point arranged outside the slope deformation range; Calculate the change between each second observation data point and the first observation data point to obtain fluctuation data; A height correction model is established based on all the aforementioned fluctuation data; The correction value of the test point is obtained using the elevation correction model, and the correction value is assigned to the initial observation data of the test point, wherein the test point is a monitoring point that needs to be corrected for elevation. The process of establishing a height correction model based on all the fluctuation data includes the following steps: performing correlation analysis on all the fluctuation data to obtain multiple analysis results; and establishing the height correction model based on the multiple analysis results using multiple regression or a neural network.

2. The elevation correction method for GNSS monitoring data of high slopes according to claim 1, characterized in that, Both the first and second observation data include elevation data and meteorological data.

3. The elevation correction method for GNSS monitoring data of high slopes according to claim 2, characterized in that, The meteorological data includes air pressure data, temperature data, and humidity data.

4. The elevation correction method for GNSS monitoring data of high slopes according to claim 1, characterized in that, The number of GNSS measuring points is positively correlated with the elevation of the monitored high slope.

5. The elevation correction method for GNSS monitoring data of high slopes according to claim 4, characterized in that, The elevation difference interval between adjacent GNSS measuring points is 30-60m.

6. The elevation correction method for GNSS monitoring data of high slopes according to claim 5, characterized in that, The range of the elevation difference interval is adjusted according to the parameters of tropospheric environmental changes.

7. The elevation correction method for GNSS monitoring data of high slopes according to claim 4, 5 or 6, characterized in that, The number of GNSS measuring points is three.

8. The elevation correction method for GNSS monitoring data of high slopes according to claim 1, characterized in that, The initial observation data of the point to be measured were obtained by differential positioning method.

9. A system for correcting the elevation of GNSS monitoring data on high slopes, characterized in that, include: The first acquisition module is used to acquire first observation data of the base station and second observation data of at least one GNSS measuring point. Among the at least one GNSS measuring point, there is a GNSS measuring point that forms an elevation difference with the base station. The GNSS measuring point is a monitoring point arranged outside the slope deformation range. The first calculation module is used to calculate the amount of change between each second observation data and the first observation data, and obtain fluctuation data respectively. The first modeling module is used to establish a height difference correction model based on all the fluctuation data. This involves performing correlation analysis on all the fluctuation data to obtain multiple analysis results; establishing the height difference correction model based on multiple analysis results using multiple regression or a neural network; and calculating the height difference correction value based on the temperature, humidity, and air pressure of the base station and monitoring points. The second calculation module is used to obtain the correction value of the point to be measured using the elevation correction model, and assign the correction value to the initial observation data of the point to be measured, wherein the point to be measured is the measuring point that needs to be corrected for elevation.

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