PPP-RTK-oriented atmospheric correction quality monitoring method and system

Abstract

The invention provides a PPP-RTK-oriented atmospheric correction quality monitoring method and system, and the method comprises the steps: extracting troposphere delay and ionosphere delay according to a PPP precision positioning method; constructing an atmospheric correction grid model according to the extracted troposphere delay and ionosphere delay; sequentially taking each station as a verification station, taking other stations as modeling stations, monitoring the atmospheric correction number of each station based on a cross validation method, and after iteration is completed, comprehensively generating an atmospheric correction quality information grid model by using monitoring results of all reference stations; and broadcasting the atmospheric correction number grid model and the atmospheric correction quality information grid model to a PPP-RTK user, so that the user side calculates the atmospheric correction number and the atmospheric correction number quality information of the current position by combining own coordinates, the atmospheric correction number grid model and the atmospheric correction quality information grid model. And the calculated atmospheric correction number and the atmospheric correction number quality information are used for PPP-RTK calculation.

Description

Technical Field

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

[0002] In recent years, the demand for high-precision positioning has been growing rapidly in mass markets 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). On the basis of fixed PPP ambiguity, it can achieve single-receiver fast centimeter-level precision positioning with the help of high-precision atmospheric delay correction numbers.

[0003] In PPP-RTK technology, atmospheric enhancement corrections (including ionospheric and tropospheric corrections) are crucial for positioning accuracy and convergence. The generation of atmospheric corrections involves two steps: estimating the atmospheric delay at the reference station and mapping it to the user station. Among them, factors such as solar activity and satellite altitude angle will affect the accuracy of the estimated atmospheric delay, resulting in an accuracy variation of 5-20 cm. In addition, under active atmospheric conditions, the error in the mapping process may also reach 1-5 cm. The above factors will cause the final atmospheric correction accuracy of the user station to vary from centimeters to decimeters. Therefore, it is necessary to monitor the atmospheric correction and mitigate the impact of abnormal atmospheric corrections on the PPP-RTK positioning accuracy. Summary of the invention

[0004] In order to further improve the accuracy and stability of atmospheric correction, thereby enhancing the precision and reliability of PPP-RTK positioning, the present invention provides a method and system for monitoring the quality of atmospheric correction numbers for PPP-RTK. By using a cross-validation method, the quality of atmospheric correction is monitored and evaluated in real time, high-quality atmospheric correction numbers are generated and used for PPP-RTK solution.

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

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

[0007] According to the extracted tropospheric delay and ionospheric delay, an atmospheric correction grid model is constructed;

[0008] Each station is used as a validation station in turn, and the other stations are used as modeling stations. The atmospheric correction number of each station is monitored 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;

[0009] The atmospheric correction grid model and the atmospheric correction quality information grid model are broadcast to PPP-RTK users, so that the user end can calculate the atmospheric correction number and the atmospheric correction number quality information of the current position by combining its own coordinates with the atmospheric correction grid model and the atmospheric correction quality information grid model, and use the calculated atmospheric correction number and the atmospheric correction number quality information for PPP-RTK solution.

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

[0011] Based on GNSS observation data, orbit, clock error and uncalibrated phase delay products, combined with GNSS observation pseudorange and carrier phase basic formula, 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] Estimating the hardware delay at the receiver end to obtain a unified benchmark atmospheric delay;

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

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

[0016]

[0017] in, represents the tropospheric delay or ionospheric delay of station r to satellite s, k represents the number of reference stations involved in the fitting; A represents the fitting coefficient; α r and β r Respectively represent the latitude and longitude of station r; α c and β c Respectively represent the latitude and longitude of the polynomial expansion point;

[0018] After fitting, the residuals are interpolated to the grid nodes using the inverse distance interpolation algorithm.

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

[0020] As a further technical solution, in one iteration of cross-validation, the atmospheric correction accuracy of the validation station Calculated as follows:

[0021]

[0022] Among them, r k Indicates a verification station; represents the atmospheric delay of the verification station generated by the modeling station; f(*) represents all the calculation processes for constructing the atmospheric correction grid model; is the true atmospheric delay at the validation station; are the coordinates of the current verification station;

[0023] After all iterations are completed, the atmospheric correction accuracy of each grid node is Calculated as follows:

[0024]

[0025] in, Represents the atmospheric correction accuracy of the verification station around the grid node.

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

[0027] The first main module is used to extract tropospheric delay and ionospheric delay according to 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 use each station as a verification station in turn, and other stations as modeling stations, to monitor the atmospheric correction number 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 quality information grid model to PPP-RTK users, so that the user end combines its own coordinates with the atmospheric correction grid model and the atmospheric correction quality information grid model to calculate the atmospheric correction number and the atmospheric correction number quality information of the current position, and use the calculated atmospheric correction number and atmospheric correction number quality information for PPP-RTK solution.

[0031] According to one aspect of the present invention specification, there is provided a server device, comprising: 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.

[0032] According to one aspect of the present invention specification, there is provided a user terminal device, comprising: 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 the atmospheric correction number quality information of the current position according to their own coordinates and the atmospheric correction number grid model and the atmospheric correction quality information grid model, and use the calculated atmospheric correction number and the atmospheric correction number quality information for PPP-RTK solution.

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

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention can monitor and evaluate the quality of atmospheric correction in real time by using a cross-validation method, thereby improving the positioning accuracy and reliability of PPP-RTK services. The method does not require additional monitoring stations and historical data, and can adapt to reference station networks of different sizes and various atmospheric conditions. In addition, by calculating and broadcasting the quality information of atmospheric correction in real time, users can perform high-precision positioning based on this information, significantly improving the accuracy and stability of positioning.

[0036] The method of the present invention can effectively reduce the influence of abnormal atmospheric correction on positioning accuracy, and improve the positioning accuracy and convergence speed of PPP-RTK. These technical effects and advantages make the method have important value and broad application prospects in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings used in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 It is a flow chart of a method for monitoring the quality of atmospheric correction numbers for PPP-RTK provided in an embodiment of the present invention.

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

[0040] Figure 3 It is a structural diagram of another atmospheric correction number quality monitoring system for PPP-RTK provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] It should be noted that:

[0042] The present invention aims at the current situation that the atmospheric correction accuracy of the prior art may vary from centimeter level to decimeter level, and it is necessary to monitor the atmospheric correction and reduce the influence of abnormal atmospheric correction on the PPP-RTK positioning accuracy. The present invention provides a PPP-RTK-oriented atmospheric correction number quality monitoring method, which evaluates the accuracy of the atmospheric correction model by selecting reference stations as verification stations in turn, and integrates the monitoring results of all reference stations to obtain the overall quality information of the atmospheric correction. The method does not require additional monitoring stations and historical data, and is applicable to reference station networks of various sizes and different atmospheric conditions.

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention are arbitrarily combined with each other to form a new technical solution. This combination is not restricted by the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that this combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0044] The present invention provides a PPP-RTK-oriented atmospheric correction number quality monitoring method, aiming to solve the problem that the prior art is difficult to evaluate the atmospheric correction number quality in real time with high precision. The atmospheric correction number quality information obtained by the monitoring method can effectively reflect the 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 the quality of atmospheric corrections for PPP-RTK. Figure 1 As shown, the overall idea is as follows:

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

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

[0048] Step 1: According to the PPP precise positioning method, extract the ionospheric delay and tropospheric delay.

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

[0050]

[0051] Where i represents the observation frequency; represents the geometric distance between satellite s and receiver r; t r and t s Represent the clock differences of the receiver and the satellite respectively; represents the ionospheric delay on the signal path; T r represents the zenith tropospheric delay; b represents the mapping function of tropospheric delay; r，i and Denotes the hardware delay of the receiver and satellite respectively; B r，i and denote the corresponding uncalibrated phase delay; λ i and denote wavelength and integer ambiguity respectively; and denote the sum of noise and multipath errors of pseudorange and carrier phase observations, respectively.

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

[0053]

[0054] in

[0055]

[0056] Both i and j represent observation frequencies; and denote the observation minus calculation of pseudorange and carrier phase respectively; represents the unit vector from the receiver to the satellite; x represents the receiver position; Indicates the receiver clock error; It represents the satellite clock error that absorbs the pseudo-range hardware delay at the satellite end; represents the ionospheric delay that absorbs the pseudorange hardware delay; γ ij represents the ionospheric coefficient of frequency i relative to frequency j; Indicates the blurriness after absorbing hardware delay; α ij and β ij Represents the ionosphere-free combination coefficient.

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

[0058] 1. Hardware Delay Estimation at the Receiver

[0059] Specifically, according to step 1, the estimated ionospheric parameters include pseudorange hardware delays from both the satellite and the receiver, which will be transmitted to PPP-RTK users through ionospheric corrections. For pseudorange hardware delays from satellites, they are independent of the reference station and remain stable over a period of time. These delays will not affect positioning. As for pseudorange hardware delays from the receiver, their effects need to be eliminated by estimating the receiver differential code bias.

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

[0061]

[0062]

[0063] Among them, p and q represent two different sites; and denote the ionospheric delay of sites p and q to satellite s respectively. In order to prevent rank deficiency in the normal equation, the sum of all DCBs of different reference stations is set to zero as a constraint, as shown below:

[0064]

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

[0066]

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

[0068] (II) Grid coefficient fitting and grid residual interpolation generation based on least squares method

[0069] Specifically, after correcting the atmospheric delay of the receiver DCB, they can be used to generate the atmospheric correction grid model. The generation process is divided into 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, represents the tropospheric delay or ionospheric delay of station r to satellite s. The tropospheric delay of all satellites at the same station is the same, while the ionospheric delay of different satellites at the same station is different; k represents the number of reference stations involved in the fitting; A represents the fitting coefficient; α r and β r Respectively represent the latitude and longitude of station r; α c and β c Respectively represent the latitude and longitude of the polynomial expansion point.

[0073] After fitting, the residuals are interpolated for the grid nodes using the inverse distance interpolation algorithm as follows:

[0074]

[0075] in, represents the delay used for linear fitting; represents the delay calculated using the fitted coefficients; Represents the fitting residual of the reference station around the grid node; Dis i Represents the distance between the reference station and the grid node; res grid Represents the residual error of the mesh node.

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

[0077]

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

[0079] Step 3: Monitor atmospheric correction data based on cross-validation method

[0080] The stations are used as verification stations in turn, and the other stations are used as modeling stations to monitor the atmospheric correction numbers of the verification stations. After the iteration is completed, all iteration results are integrated to generate a grid model of atmospheric correction quality information.

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

[0082]

[0083] Among them, r k Indicates a verification station; represents the atmospheric delay of the verification station generated by the modeling station; f(*) represents all the calculation processes in step 2; is the true atmospheric delay at the validation station; is the coordinate of the current verification station. After all iterations are completed, the atmospheric correction accuracy of each grid node is Calculated as follows:

[0084]

[0085] in, Represents the atmospheric correction accuracy of the verification station around the grid node.

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

[0087] Step 5: On the user side, the user calculates the atmospheric correction number and atmospheric correction number quality information of the current position based on its own coordinates and the received atmospheric correction number grid model and atmospheric correction number quality information grid model. These atmospheric correction numbers and atmospheric correction number quality information are used for PPP-RTK solution to achieve high-precision positioning.

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

[0089]

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

[0091] The user-side atmospheric correction quality information (Quality Indicator, QI) can be calculated according to the following formula:

[0092]

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

[0094] Considering that users need to eliminate the influence of hardware delay on ionospheric correction through single difference between satellites, the ionospheric and tropospheric QI values ​​actually used by users are calculated according to the following formula:

[0095]

[0096] in, and represent the QI values ​​of ionospheric and tropospheric corrections, respectively; and denote ionospheric and tropospheric corrections, respectively; and T est represents the ionospheric and tropospheric delays in the user station PPP estimate. ion，min and σ trop,min Represent the minimum error thresholds for the ionosphere and troposphere, respectively. These thresholds are mainly to prevent matrix anomalies in the estimation process and are usually set to small values.

[0097] The implementation basis of each embodiment of the present invention is to implement programmed processing through a device with a processor function. Therefore, in engineering practice, the technical solutions and functions of each embodiment of the present invention are encapsulated into various modules. Based on this reality, on the basis of each of the above embodiments, an embodiment of the present invention provides 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 embodiment.

[0098] See also Figure 2The system includes: a first main module, which is used to extract tropospheric delay and ionospheric delay according to the PPP precise positioning method; a second main module, which is used to construct an atmospheric correction number grid model according to the extracted tropospheric delay and ionospheric delay; a third main module, which is used to use each station as a verification station in turn and other stations as modeling stations, monitor the atmospheric correction number of each station based on a cross-validation method, and after the iteration is completed, comprehensively generate an atmospheric correction quality information grid model based on the monitoring results of all reference stations; a fourth main module, which is used to broadcast the atmospheric correction number grid model and the atmospheric correction quality information grid model to PPP-RTK users, so that the user end combines its own coordinates with the atmospheric correction number grid model and the atmospheric correction quality information grid model to calculate the atmospheric correction number and atmospheric correction number quality information of the current position, and use the calculated atmospheric correction number and atmospheric correction number quality information for PPP-RTK solution.

[0099] The atmospheric correction number quality monitoring system for PPP-RTK provided by the embodiment of the present invention solves the problem that the existing technology is difficult to evaluate the atmospheric correction number quality in real time with high precision. Figure 2 Several modules in it use cross-validation methods to monitor and evaluate the quality of atmospheric correction in real time, generate high-quality atmospheric correction numbers and serve them for PPP-RTK solution.

[0100] It should be noted that the system embodiments provided by the present invention are not only used to implement the methods in the above-mentioned method embodiments, but also used to implement the methods in other method embodiments provided by the present invention. The only difference lies in the setting of corresponding functional modules, and the principles thereof are basically the same as the principles of the above-mentioned system embodiments provided by the present invention. As long as technical personnel in this field refer to the specific technical solutions in other method embodiments on the basis of the above-mentioned system embodiments, obtain corresponding technical means and technical solutions composed of these technical means by combining technical features, and on the premise of ensuring the practicality of the technical solutions, they will improve the modules in the above-mentioned system embodiments to obtain corresponding system class embodiments for implementing the methods in other method class embodiments.

[0101] Based on the same inventive concept as the aforementioned embodiment, an embodiment of the present invention also provides a server-side device, comprising: one or more processors; a storage device for storing one or more programs; when 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 aforementioned embodiment, an embodiment of the present invention further provides a user terminal device, comprising: 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 the atmospheric correction number quality information of the current position according to their own coordinates and the atmospheric correction number grid model and the atmospheric correction quality information grid model, and use the calculated atmospheric correction number and the atmospheric correction number quality information for PPP-RTK solution.

[0103] Based on the same inventive concept as the aforementioned embodiment, the embodiment of the present invention further provides a PPP-RTK-oriented atmospheric correction number quality monitoring system, including the aforementioned server-side device and the aforementioned user-side device.

[0104] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0105] In summary, the present invention provides a method for monitoring the quality of atmospheric corrections for PPP-RTK. At the service end, according to the PPP precise positioning method, ionospheric delay and tropospheric delay are extracted; an atmospheric correction grid model is constructed, including hardware delay estimation at the receiver end, grid coefficient fitting based on the least squares method, and grid residual interpolation generation; atmospheric corrections are monitored based on a cross-validation method, and the stations are sequentially used as verification stations, and other stations are used as modeling stations to monitor the atmospheric corrections of the verification stations. After the iteration is completed, the monitoring results of all reference stations are integrated to generate an atmospheric correction quality information grid model; the generated atmospheric correction grid model and atmospheric correction quality information grid model are broadcast to PPP-RTK users. At the user end, the user calculates the atmospheric corrections and atmospheric correction quality information of the current position according to its own coordinates, as well as the received atmospheric correction grid model and atmospheric correction quality information grid model. These atmospheric corrections and atmospheric correction quality information are used for PPP-RTK solution to achieve high-precision positioning.

[0106] The terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions, for example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to the steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the quality of atmospheric corrections for PPP-RTK, characterized in that: include: According to the PPP precise positioning method, the tropospheric delay and ionospheric delay are extracted; According to the extracted tropospheric delay and ionospheric delay, an atmospheric correction grid model is constructed; Each station is used as a validation station in turn, and the other stations are used as modeling stations. The atmospheric correction number of each station is monitored 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 atmospheric correction grid model and the atmospheric correction quality information grid model are broadcast to PPP-RTK users, so that the user end can calculate the atmospheric correction number and the atmospheric correction number quality information of the current position by combining its own coordinates with the atmospheric correction grid model and the atmospheric correction quality information grid model, and use the calculated atmospheric correction number and the atmospheric correction number quality information for PPP-RTK solution.

2. The atmospheric correction number quality monitoring method for PPP-RTK according to claim 1, characterized in that: According to the PPP precise positioning method, the tropospheric delay and ionospheric delay are extracted, including: Based on GNSS observation data, orbit, clock error and uncalibrated phase delay products, combined with GNSS observation pseudorange and carrier phase basic formula, 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: According to the extracted tropospheric delay and ionospheric delay, an atmospheric correction grid model is constructed, including: Estimating the hardware delay at the receiver end to obtain a unified benchmark atmospheric delay; Based on the unified benchmark atmospheric delay, the least squares grid coefficient fitting and grid residual interpolation are performed to form an atmospheric correction grid model.

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

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 residuals of the grid nodes to the PPP-RTK users for use in atmospheric delay calculation of the 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 is Calculated as follows: Among them, r k Indicates a verification station; represents the atmospheric delay of the verification station generated by the modeling station; f(*) represents all the calculation processes for constructing the atmospheric correction grid model; is the true atmospheric delay at the validation station; are the coordinates of the current verification station; After all iterations are completed, the atmospheric correction accuracy of each grid node is Calculated as follows: in, Represents the atmospheric correction accuracy of the verification station around the grid node.

7. The atmospheric correction quality monitoring system for PPP-RTK is characterized by: include: The first main module is used to extract tropospheric delay and ionospheric delay according to 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 use each station as a verification station in turn, and other stations as modeling stations, to monitor the atmospheric correction number 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 quality information grid model to PPP-RTK users, so that the user end combines its own coordinates with the atmospheric correction grid model and the atmospheric correction quality information grid model to calculate the atmospheric correction number and the atmospheric correction number quality information of the current position, and use the calculated atmospheric correction number and atmospheric correction number quality information for PPP-RTK solution.

8. A server device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When 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 as described in any one of claims 1 to 6.

9. 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 calculate the atmospheric correction number and the atmospheric correction number quality information of the current position according to their own coordinates and the atmospheric correction number grid model and the atmospheric correction number quality information grid model, and use the calculated atmospheric correction number and atmospheric correction number quality information for PPP-RTK solution.

10. The atmospheric correction quality monitoring system for PPP-RTK is characterized by: It includes the server-side device described in claim 8 and the user-side device described in claim 9.

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