PPP-rtk-oriented atmospheric correction number quality monitoring method and system

Abstract

The application provides a method and system for monitoring the quality of atmospheric correction numbers for PPP-RTK, which comprises the following steps: extracting tropospheric delay and ionospheric delay according to the PPP precise positioning method; constructing an atmospheric correction number grid model according to the extracted tropospheric delay and ionospheric delay; taking each site as a verification station in turn and other sites as modeling stations, and monitoring the atmospheric correction numbers of each site based on the cross-validation method; after iteration is completed, synthesizing the monitoring results of all reference stations to generate an atmospheric correction quality information grid model; and broadcasting the atmospheric correction number grid model and the atmospheric correction quality information grid model to the PPP-RTK users, so that the users can combine their own coordinates with the atmospheric correction number grid model and the atmospheric correction quality information grid model to calculate the atmospheric correction numbers and atmospheric correction quality information of the current position, and use the calculated atmospheric correction numbers and atmospheric correction quality information for PPP-RTK calculation.

Description

Technical Field

[0001] This invention belongs to the field of high-precision positioning technology of global navigation satellite system (GNSS), and more specifically, relates to a method and system for atmospheric correction number quality monitoring for PPP-RTK. Background Technology

[0002] In recent years, the demand for high-precision positioning has been growing rapidly in the mass market and automation applications. PPP-RTK technology (Precise Point Positioning-Real-Time Kinematic) combines the advantages of Precise Point Positioning (PPP) and Real-Time Kinematic (RTK). Based on the fixed ambiguity of PPP, it can achieve rapid centimeter-level precise positioning with a single receiver by using high-precision atmospheric delay corrections for constraint.

[0003] In PPP-RTK technology, atmospheric enhancement corrections (including ionospheric and tropospheric corrections) are crucial for positioning accuracy and convergence. Generating atmospheric corrections involves two steps: estimating the atmospheric delay at a reference station and mapping it to the user station. Factors such as solar activity and satellite elevation angle can affect the accuracy of the estimated atmospheric delay, leading to accuracy variations of 5-20 centimeters. Furthermore, under active atmospheric conditions, the mapping process error can reach 1-5 centimeters. These factors can cause the final atmospheric correction accuracy at the user station to vary from centimeters to decimeters. Therefore, it is necessary to monitor atmospheric corrections and mitigate the impact of anomalous atmospheric corrections on PPP-RTK positioning accuracy. Summary of the Invention

[0004] To further improve the accuracy and stability of atmospheric corrections, thereby enhancing the precision and reliability of PPP-RTK positioning, this invention provides a method and system for monitoring the quality of atmospheric corrections for PPP-RTK. By using cross-validation, the quality of atmospheric corrections is monitored and evaluated in real time, generating high-quality atmospheric corrections that can then be used for PPP-RTK calculations.

[0005] According to one aspect of the present invention, a method for monitoring atmospheric correction numbers for PPP-RTK is provided, comprising:

[0006] Based on the PPP precise positioning method, tropospheric delay and ionospheric delay are extracted;

[0007] Based on the extracted tropospheric delay and ionospheric delay, an atmospheric correction grid model is constructed.

[0008] Each station was used as a validation station in turn, and the other stations were used as modeling stations. The atmospheric corrections of each station were monitored based on the cross-validation method. After the iteration was completed, the monitoring results of all reference stations were combined to generate an atmospheric correction quality information grid model.

[0009] The atmospheric correction grid model and atmospheric correction mass information grid model are broadcast to PPP-RTK users. The users can then use their own coordinates and the atmospheric correction grid model and atmospheric correction mass information grid model to calculate the atmospheric correction and atmospheric correction mass information of the current location. The calculated atmospheric correction and atmospheric correction mass information are then used for PPP-RTK solution.

[0010] As a further technical solution, based on the PPP precise positioning method, the tropospheric delay and ionospheric delay are extracted, including:

[0011] Based on GNSS observation data, orbit, clock bias, and uncalibrated phase delay products, and combined with the basic formulas for GNSS observation pseudorange and carrier phase, ionospheric delay and tropospheric delay are extracted.

[0012] As a further technical solution, an atmospheric correction grid model is constructed based on the extracted tropospheric delay and ionospheric delay, including:

[0013] Hardware delay estimation is performed at the receiver end to obtain an atmospheric delay with a unified reference.

[0014] Based on a unified benchmark atmospheric delay, least squares grid coefficient fitting and grid residual interpolation are performed to generate an atmospheric correction grid model.

[0015] As a further technical solution, the least squares grid coefficient fitting is expressed as follows:

[0016]

[0017] in, The tropospheric or ionospheric delay of station r relative to satellite s is represented by r, k represents the number of reference stations involved in the fitting, A represents the fitting coefficient, and α represents the tropospheric or ionospheric delay. r and β r Representing the latitude and longitude of station r respectively; α c and β c These represent the latitude and longitude of the polynomial expansion point, respectively;

[0018] After fitting, the inverse distance interpolation algorithm is used to perform residual interpolation on the grid nodes.

[0019] As a further technical solution, the method also includes: broadcasting the fitting coefficients and the residuals of the grid nodes to PPP-RTK users for atmospheric delay calculation by PPP-RTK users.

[0020] As a further technical solution, in one iteration of cross-validation, the atmospheric correction accuracy of the validation station was improved. Calculate using the following formula:

[0021]

[0022] Where, r k Indicates a verification station; f(*) represents the atmospheric delay of the validation station generated by the modeling station; f(*) represents all the calculations involved in building the atmospheric correction grid model. It is the actual atmospheric delay at the verification station; These are the coordinates of the current verification station;

[0023] After all iterations are completed, the atmospheric correction accuracy for each grid node is... Calculate using the following formula:

[0024]

[0025] in, This indicates the atmospheric correction accuracy of the verification stations surrounding the grid nodes.

[0026] According to one aspect of the present invention, an atmospheric correction number quality monitoring system for PPP-RTK is provided, comprising:

[0027] The first main module is used to extract tropospheric delay and ionospheric delay based on the PPP precise positioning method;

[0028] The second main module is used to construct an atmospheric correction grid model based on the extracted tropospheric delay and ionospheric delay.

[0029] The third main module is used to take each station as a verification station in turn and other stations as modeling stations. It monitors the atmospheric corrections of each station based on the cross-validation method. After the iteration is completed, the monitoring results of all reference stations are integrated to generate an atmospheric correction quality information grid model.

[0030] The fourth main module is used to broadcast the atmospheric correction grid model and the atmospheric correction mass information grid model to PPP-RTK users. The user terminal combines its own coordinates with the atmospheric correction grid model and the atmospheric correction mass information grid model to calculate the atmospheric correction number and atmospheric correction mass information of the current location, and uses the calculated atmospheric correction number and atmospheric correction mass information for PPP-RTK solution.

[0031] According to one aspect of the present invention, a server device is provided, comprising: one or more processors; a storage device for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the PPP-RTK-oriented atmospheric correction number quality monitoring method.

[0032] According to one aspect of the present invention, a user terminal device is provided, comprising: one or more processors; a receiving device for receiving one or more input data; when the one or more input data is executed by the one or more processors, the one or more processors calculate atmospheric corrections and atmospheric correction mass information at the current location based on their own coordinates, an atmospheric correction grid model, and an atmospheric correction mass information grid model, and use the calculated atmospheric corrections and atmospheric correction mass information for PPP-RTK solution.

[0033] According to one aspect of the present invention, an atmospheric correction number quality monitoring system for PPP-RTK is provided, such as... Figure 3 As shown, it includes the server-side device and the user-side device.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0035] This invention utilizes cross-validation to monitor and evaluate the quality of atmospheric corrections in real time, thereby improving the positioning accuracy and reliability of PPP-RTK services. This method requires no additional monitoring stations or historical data and can adapt to reference station networks of varying sizes and atmospheric conditions. Furthermore, by calculating and broadcasting atmospheric correction quality information in real time, users can perform high-precision positioning based on this information, significantly improving positioning accuracy and stability.

[0036] The method of this invention can effectively reduce the impact of anomalous atmospheric corrections on positioning accuracy, improving both the positioning accuracy and convergence speed of PPP-RTK. These technical effects and advantages make this method of significant value and broad application prospects in practical applications. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating the atmospheric correction number quality monitoring method for PPP-RTK provided in this embodiment of the invention.

[0039] Figure 2 This is a schematic diagram of the atmospheric correction number quality monitoring system for PPP-RTK provided in an embodiment of the present invention.

[0040] Figure 3 This is a schematic diagram of another atmospheric correction number quality monitoring system for PPP-RTK provided in an embodiment of the present invention. Detailed Implementation

[0041] It should be noted that:

[0042] This invention addresses the current situation where existing atmospheric correction accuracies can range from centimeter to decimeter levels, necessitating the monitoring of atmospheric corrections and mitigating the impact of anomalous atmospheric corrections on PPP-RTK positioning accuracy. It provides a method for monitoring the quality of atmospheric corrections for PPP-RTK. This method evaluates the accuracy of the atmospheric correction model by sequentially selecting reference stations as validation stations, and then synthesizes the monitoring results from all reference stations to derive the overall quality information of the atmospheric corrections. This method requires no additional monitoring stations or historical data and is applicable to reference station networks of various sizes and different atmospheric conditions.

[0043] 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, 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. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0044] This invention provides an atmospheric correction mass monitoring method for PPP-RTK, aiming to solve the problem of existing technologies' difficulty in accurately and in real-time assessing atmospheric correction mass. The atmospheric correction mass information obtained by this monitoring method can effectively reflect centimeter-level changes in atmospheric correction accuracy, and can significantly improve the positioning performance of PPP-RTK.

[0045] This implementation provides a method for monitoring atmospheric corrected mass air quality using PPP-RTK, such as... Figure 1 As shown, the overall approach is as follows:

[0046] On the server side, precise point positioning is first performed using GNSS observation data from the reference station, precise orbit and clock bias products, and uncalibrated phase delay products. Tropospheric and ionospheric delays are then extracted from the positioning results. Subsequently, the ionospheric delay information is used to estimate the receiver differential code bias (DCB) of the reference station, thereby standardizing the ionospheric delay. Based on these atmospheric delays, atmospheric correction grid modeling and cross-validation quality monitoring are performed. The atmospheric correction grid model and atmospheric correction quality information grid model are then broadcast to users. On the user side, users calculate atmospheric corrections and atmospheric correction quality information for their current location based on the atmospheric correction grid model and atmospheric correction quality information grid model. Finally, this atmospheric correction and quality information is used in PPP-RTK to achieve high-precision positioning.

[0047] The method described in this embodiment of the invention specifically includes the following steps:

[0048] Step 1: Extract the ionospheric delay and tropospheric delay according to the PPP precise positioning method.

[0049] Specifically, the original GNSS pseudorange observations mentioned in step 1 and carrier phase observations It can be represented as follows:

[0050]

[0051] Where i represents the observation frequency; t represents the geometric distance between satellite s and receiver r; r and t s These represent the clock biases of the receiver and the satellite, respectively. Indicates the ionospheric delay along the signal path; T r Indicates zenith tropospheric delay; The mapping function representing tropospheric delay; b r，i and B represents the hardware delay of the receiver and the satellite, respectively; r，i and These represent the corresponding uncalibrated phase delays; λ i and These represent wavelength and integer ambiguity, respectively. and These represent the sum of noise and multipath error of the pseudorange and carrier phase observations, respectively.

[0052] After using precision orbit and clock error products, the linearized dual-frequency observation equations can be expressed as follows:

[0053]

[0054] in

[0055]

[0056] Both i and j represent the observation frequency; and These represent the observation subtraction calculations for pseudorange and carrier phase, respectively; represents the unit vector from the receiver to the satellite; x represents the receiver's position; Indicates receiver clock bias; This indicates the satellite clock bias that incorporates the pseudorange hardware delay at the satellite end; This represents the ionospheric delay that absorbs the pseudorange hardware delay; γ ij This represents the ionospheric coefficient of frequency i relative to frequency j; This indicates ambiguity that incorporates hardware latency; α ij and β ij This represents the combination coefficient without an ionosphere.

[0057] Step 2: Construct an atmospheric correction grid model, including hardware delay estimation at the receiver, grid coefficient fitting based on least squares method, and grid residual interpolation generation.

[0058] (a) Hardware delay estimation at the receiver end

[0059] Specifically, according to step 1, the estimated ionospheric parameters include pseudorange hardware delays from both the satellite and the receiver. These delays will be transmitted to the PPP-RTK user via ionospheric correction. The pseudorange hardware delays from the satellite are independent of the reference station and remain stable over a period of time. These delays do not affect positioning. As for the pseudorange hardware delays from the receiver, their impact needs to be eliminated by estimating the receiver differential code bias.

[0060] The consistency of receiver hardware delay absorbed in ionospheric correction is ensured by estimating the receiver differential code bias (DCB). The formula for DCB estimation can be expressed as:

[0061]

[0062]

[0063] Here, p and q represent two different sites; and Let p and q represent the ionospheric delays of stations p and q relative to satellite s, respectively. To prevent rank deficiency in the normal equations, the sum of all DCBs from different reference stations is set to zero as a constraint, as shown below:

[0064]

[0065] After DCB estimation, the ionospheric delay that ensures consistent hardware delay absorption can be expressed as:

[0066]

[0067] Among them, DCB const This indicates the calibrated receiver DCB.

[0068] (II) Generation of Grid Coefficients Based on Least Squares Method and Grid Residual Interpolation

[0069] Specifically, after correcting for atmospheric delay in the receiver DCB, these corrections can be used to generate an atmospheric correction grid model. The generation process consists of two steps: low-order linear coefficient fitting based on the least squares method and residual interpolation after fitting.

[0070] The low-order linear coefficient fitting method based on the least squares method can be expressed as:

[0071]

[0072] in, denoted by r, it represents the tropospheric or ionospheric delay of station r relative to satellite s. All satellites at the same station have the same tropospheric delay, while different satellites at the same station have different ionospheric delays; k represents the number of reference stations involved in the fitting; A represents the fitting coefficient; α r and β r Representing the latitude and longitude of station r respectively; α c and β c These represent the latitude and longitude of the polynomial expansion point, respectively.

[0073] After fitting, the inverse distance interpolation algorithm is used to perform residual interpolation on the grid nodes, as shown below:

[0074]

[0075] in, This represents the delay used for linear fitting; This represents the delay calculated using the fitting coefficients; Dis represents the fitting residuals of the reference stations surrounding the grid nodes. i Represents the distance between the reference station and the grid node; res grid This represents the residual of a grid node.

[0076] Finally, the atmospheric delay at the user end can be calculated using the fitting coefficients and the residuals of the grid nodes, as shown below:

[0077]

[0078] in, This represents the delay calculated using fitting coefficients based on the user's latitude and longitude; This represents the residuals of the four grid nodes surrounding the user; This indicates the distance between the user and the grid node.

[0079] Step 3: Monitor atmospheric corrections using cross-validation method

[0080] The stations were sequentially used as validation stations, and the other stations as modeling stations. The atmospheric correction values ​​at the validation stations were monitored. After the iterations were completed, all iteration results were combined to generate an atmospheric correction quality information grid model.

[0081] Specifically, after generating the atmospheric correction grid model, cross-validation is performed to monitor the quality of these corrections. This method includes two steps: cross-validation and generation of the atmospheric correction quality information grid model. In cross-validation, a site is assigned as a validation station and other modeling stations, and this process is repeated until each station has served as a validation station once. In one iteration of cross-validation, the atmospheric correction accuracy of the validation station is... It can be calculated using the following formula:

[0082]

[0083] Where, r k Indicates a verification station; f(*) represents the atmospheric delay of the verification station generated by the modeling station; f(*) represents all calculations in step 2. It is the actual atmospheric delay at the verification station; These are the coordinates of the current verification station. After all iterations are completed, the atmospheric correction accuracy for each grid node is... Calculate using the following formula:

[0084]

[0085] in, This indicates the atmospheric correction accuracy of the verification stations surrounding the grid nodes.

[0086] Step 4: On the server side, broadcast the atmospheric correction data grid model and atmospheric correction quality information grid model generated in the above steps to PPP-RTK users.

[0087] Step 5: On the user's end, the user calculates the atmospheric correction and atmospheric correction quality information for the current location based on their own coordinates and the received atmospheric correction grid model and atmospheric correction quality information. These atmospheric corrections and atmospheric correction quality information are used for PPP-RTK calculation to achieve high-precision positioning.

[0088] Specifically, the atmospheric delay at the user end can be calculated using the fitting coefficients and the residuals of the grid nodes, as shown below:

[0089]

[0090] in, This represents the delay calculated using fitting coefficients based on the user's latitude and longitude; This represents the residuals of the four grid nodes surrounding the user; This indicates the distance between the user and the grid node.

[0091] The corrected atmospheric quality indicator (QI) for users can be calculated using the following formula:

[0092]

[0093] in, This indicates the atmospheric correction accuracy of the four grid points surrounding the user; This indicates the distance between the user and the grid node.

[0094] Considering that users need to eliminate the impact of hardware delay on ionospheric corrections through inter-satellite single-difference, the actual ionospheric and tropospheric QI values ​​used by users are calculated using the following formula:

[0095]

[0096] in, and These represent the QI values ​​corrected for the ionosphere and troposphere, respectively. and These represent corrections for the ionosphere and troposphere, respectively. and T est This represents the ionospheric and tropospheric delays in the PPP estimation for user stations. σ ion，min and σ trop,min These represent the minimum error thresholds for the ionosphere and troposphere, respectively. These thresholds are primarily designed to prevent matrix anomalies during the estimation process and are typically set to small values.

[0097] The implementation of the various embodiments of the present invention is based on programmed processing by a device with processor functionality. Therefore, in practical engineering, the technical solutions and functions of the various embodiments of the present invention are encapsulated into various modules. Based on this reality, and building upon the above embodiments, the embodiments of the present invention provide an atmospheric correction number quality monitoring system for PPP-RTK, which is used to execute the atmospheric correction number quality monitoring method for PPP-RTK in the above method embodiments.

[0098] See Figure 2The system includes: a first main module for extracting tropospheric and ionospheric delays using the PPP precise positioning method; a second main module for constructing an atmospheric correction grid model based on the extracted tropospheric and ionospheric delays; a third main module for monitoring atmospheric corrections at each station using cross-validation methods, with each station serving as a verification station and the others as modeling stations, and after iteration, integrating the monitoring results from all reference stations to generate an atmospheric correction mass information grid model; and a fourth main module for broadcasting the atmospheric correction grid model and the atmospheric correction mass information grid model to PPP-RTK users, allowing users to calculate the atmospheric corrections and atmospheric correction mass information at their current location by combining their own coordinates with the atmospheric correction grid model and the atmospheric correction mass information grid model, and then using the calculated atmospheric corrections and atmospheric correction mass information for PPP-RTK calculations.

[0099] The atmospheric correction number quality monitoring system for PPP-RTK provided in this invention addresses the problem of existing technologies' difficulty in accurately and in real-time assessing atmospheric correction number quality. Figure 2 Several modules in the system use cross-validation to monitor and evaluate the quality of atmospheric corrections in real time, generate high-quality atmospheric corrections, and make them serve PPP-RTK solutions.

[0100] It should be noted that the system embodiments provided by the present invention are used not only to implement the methods in the above method embodiments, but also to implement the methods in other method embodiments provided by the present invention. The only difference is that corresponding functional modules are set. The principle is basically the same as that of the above system embodiments provided by the present invention. As long as those skilled in the art can improve the modules in the above system embodiments by referring to the specific technical solutions in other method embodiments and combining technical features to obtain corresponding technical means and technical solutions composed of these technical means, on the basis of the above system embodiments, and on the premise of ensuring the practicality of the technical solutions, they can obtain corresponding system-like embodiments for implementing the methods in other method-like embodiments.

[0101] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides a server device, including: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the atmospheric correction number quality monitoring method for PPP-RTK.

[0102] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides a user terminal device, including: one or more processors; a receiving device for receiving one or more input data; when the one or more input data are executed by the one or more processors, the one or more processors calculate the atmospheric correction number and atmospheric correction number quality information of the current position according to their own coordinates, an atmospheric correction number grid model, and an atmospheric correction number quality information grid model, and use the calculated atmospheric correction number and atmospheric correction number quality information for PPP-RTK solution.

[0103] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides an atmospheric correction number quality monitoring system for PPP-RTK, including the aforementioned server-side equipment and the aforementioned user-side equipment.

[0104] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0105] In summary, this invention provides an atmospheric correction number quality monitoring method for PPP-RTK. At the server end, ionospheric delay and tropospheric delay are extracted based on the PPP precise positioning method. An atmospheric correction number grid model is constructed, including hardware delay estimation at the receiver end, grid coefficient fitting based on least squares, and grid residual interpolation generation. Atmospheric correction numbers are monitored using a cross-validation method, with each station sequentially serving as a validation station and other stations as modeling stations. The atmospheric correction numbers at the validation stations are monitored, and after iteration, the monitoring results from all reference stations are integrated to generate an atmospheric correction number quality information grid model. The generated atmospheric correction number grid model and atmospheric correction number quality information grid model are broadcast to PPP-RTK users. At the user end, the user calculates the atmospheric correction number and atmospheric correction number quality information for their current location based on their own coordinates and the received atmospheric correction number grid model and atmospheric correction number quality information grid model. This atmospheric correction number and atmospheric correction number quality information are used for PPP-RTK calculation to achieve high-precision positioning.

[0106] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring atmospheric correction numbers for PPP-RTK, characterized in that, include: Based on the PPP precise positioning method, the tropospheric delay and ionospheric delay are extracted; Based on the extracted tropospheric delay and ionospheric delay, an atmospheric correction grid model is constructed. Each station was used as a validation station in turn, and the other stations were used as modeling stations. The atmospheric corrections of each station were monitored based on the cross-validation method. After the iteration was completed, the monitoring results of all reference stations were combined to generate an atmospheric correction quality information grid model. The atmospheric correction grid model and atmospheric correction mass information grid model are broadcast to PPP-RTK users, so that the user terminal can combine its own coordinates with the atmospheric correction grid model and atmospheric correction mass information grid model to calculate the atmospheric correction number and atmospheric correction mass information of the current location, and use the calculated atmospheric correction number and atmospheric correction mass information for PPP-RTK solution; Atmospheric correction mass information is calculated using the following formula: in, This indicates the atmospheric correction accuracy of the four grid points surrounding the user; Indicates the distance between the user and the grid node; The actual QI values ​​of the ionosphere and troposphere used by users are calculated using the following formula: in, and QI user,trop These represent the QI values ​​corrected for the ionosphere and troposphere, respectively. and These represent corrections for the ionosphere and troposphere, respectively. and T est σ represents the ionospheric and tropospheric delays in the PPP estimation of user stations. ion,min and σ trop,min These represent the minimum error thresholds for the ionosphere and troposphere, respectively.

2. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 1, characterized in that, Based on the PPP precise positioning method, the tropospheric delay and ionospheric delay are extracted, including: Based on GNSS observation data, orbit, clock bias, and uncalibrated phase delay products, and combined with the basic formulas for GNSS observation pseudorange and carrier phase, ionospheric delay and tropospheric delay are extracted.

3. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 1, characterized in that, Based on the extracted tropospheric and ionospheric delays, an atmospheric corrected grid model is constructed, including: Hardware delay estimation is performed at the receiver end to obtain an atmospheric delay with a unified reference. Based on a unified benchmark atmospheric delay, least squares grid coefficient fitting and grid residual interpolation are performed to generate an atmospheric correction grid model.

4. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 3, characterized in that, The least squares grid coefficient fitting is expressed as follows: in, The tropospheric or ionospheric delay of station r relative to satellite s is represented by r, k represents the number of reference stations involved in the fitting, A represents the fitting coefficient, and α represents the tropospheric or ionospheric delay. r and β r Representing the latitude and longitude of station r respectively; α c and β c These represent the latitude and longitude of the polynomial expansion point, respectively; After fitting, the inverse distance interpolation algorithm is used to perform residual interpolation on the grid nodes.

5. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 4, characterized in that, The method further includes: broadcasting the fitting coefficients and the residuals of the grid nodes to PPP-RTK users for atmospheric delay calculation by PPP-RTK users.

6. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 1, characterized in that, In one iteration of cross-validation, the atmospheric correction accuracy of the validation station... Calculate using the following formula: Where, r k Indicates a verification station; f(*) represents the atmospheric delay of the validation station generated by the modeling station; f(*) represents all the calculations involved in building the atmospheric correction grid model. It is the actual atmospheric delay at the verification station; These are the coordinates of the current verification station; After all iterations are completed, the atmospheric correction accuracy for each grid node is... Calculate using the following formula: in, This indicates the atmospheric correction accuracy of the verification stations surrounding the grid nodes.

7. An atmospheric correction number quality monitoring system for PPP-RTK, used to implement the method as described in any one of claims 1-6, characterized in that, include: The first main module is used to extract tropospheric delay and ionospheric delay based on the PPP precise positioning method; The second main module is used to construct an atmospheric correction grid model based on the extracted tropospheric delay and ionospheric delay. The third main module is used to take each station as a verification station in turn and other stations as modeling stations. It monitors the atmospheric corrections of each station based on the cross-validation method. After the iteration is completed, the monitoring results of all reference stations are integrated to generate an atmospheric correction quality information grid model. The fourth main module is used to broadcast the atmospheric correction grid model and the atmospheric correction mass information grid model to PPP-RTK users. The user terminal combines its own coordinates with the atmospheric correction grid model and the atmospheric correction mass information grid model to calculate the atmospheric correction number and atmospheric correction mass information of the current location, and uses the calculated atmospheric correction number and atmospheric correction mass information for PPP-RTK solution.

8. A user terminal device, characterized in that, include: One or more processors; A receiving device for receiving one or more input data; When one or more input data are executed by the one or more processors, the one or more processors implement the steps of the atmospheric correction number quality monitoring method for PPP-RTK as described in any one of claims 1-6.

9. An atmospheric correction number quality monitoring system for PPP-RTK, characterized in that, It includes server-side equipment and the user-side equipment as described in claim 8.

Images